Dissertations / Theses: 'User profile'

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Boc, Michaël Mathias. "Profile of mobility : user-centric networking." Paris 6, 2009. http://www.theses.fr/2009PA066355.

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Limam, Lyes. "Usage-driven unified model for user profile and data source profile extraction." Thesis, Lyon, INSA, 2014. http://www.theses.fr/2014ISAL0058/document.

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La problématique traitée dans la thèse s’inscrit dans le cadre de l’analyse d’usage dans les systèmes de recherche d’information. En effet, nous nous intéressons à l’utilisateur à travers l’historique de ses requêtes, utilisées comme support d’analyse pour l’extraction d'un profil d’usage. L’objectif est de caractériser l’utilisateur et les sources de données qui interagissent dans un réseau afin de permettre des comparaisons utilisateur-utilisateur, source-source et source-utilisateur. Selon une étude que nous avons menée sur les travaux existants sur les modèles de profilage, nous avons conclu que la grande majorité des contributions sont fortement liés aux applications dans lesquelles ils étaient proposés. En conséquence, les modèles de profils proposés ne sont pas réutilisables et présentent plusieurs faiblesses. Par exemple, ces modèles ne tiennent pas compte de la source de données, ils ne sont pas dotés de mécanismes de traitement sémantique et ils ne tiennent pas compte du passage à l’échelle (en termes de complexité). C'est pourquoi, nous proposons dans cette thèse un modèle d’utilisateur et de source de données basé sur l’analyse d’usage. Les caractéristiques de ce modèle sont les suivantes. Premièrement, il est générique, permettant de représenter à la fois un utilisateur et une source de données. Deuxièmement, il permet de construire le profil de manière implicite à partir de l’historique de requêtes de recherche. Troisièmement, il définit le profil comme un ensemble de centres d’intérêts, chaque intérêt correspondant à un cluster sémantique de mots-clés déterminé par un algorithme de clustering spécifique. Et enfin, dans ce modèle le profil est représenté dans un espace vectoriel. Les différents composants du modèle sont organisés sous la forme d’un Framework, la complexité de chaque composant y est évaluée. Le Framework propose : - une méthode pour la désambigüisation de requêtes; - une méthode pour la représentation sémantique des logs sous la forme d’une taxonomie ; - un algorithme de clustering qui permet l’identification rapide et efficace des centres d’intérêt représentés par des clusters sémantiques de mots clés ; - une méthode pour le calcul du profil de l’utilisateur et du profil de la source de données à partir du modèle générique. Le Framework proposé permet d'effectuer différentes tâches liées à la structuration d’un environnement distribué d’un point de vue usage. Comme exemples d’application, le Framework est utilisé pour la découverte de communautés d’utilisateurs et la catégorisation de sources de données. Pour la validation du Framework, une série d’expérimentations est menée en utilisant des logs du moteur de recherche AOL-search, qui ont démontrées l’efficacité de la désambigüisation sur des requêtes courtes, et qui ont permis d’identification de la relation entre le clustering basé sur une fonction de qualité et le clustering basé sur la structure
This thesis addresses a problem related to usage analysis in information retrieval systems. Indeed, we exploit the history of search queries as support of analysis to extract a profile model. The objective is to characterize the user and the data source that interact in a system to allow different types of comparison (user-to-user, source-to-source, user-to-source). According to the study we conducted on the work done on profile model, we concluded that the large majority of the contributions are strongly related to the applications within they are proposed. As a result, the proposed profile models are not reusable and suffer from several weaknesses. For instance, these models do not consider the data source, they lack of semantic mechanisms and they do not deal with scalability (in terms of complexity). Therefore, we propose a generic model of user and data source profiles. The characteristics of this model are the following. First, it is generic, being able to represent both the user and the data source. Second, it enables to construct the profiles in an implicit way based on histories of search queries. Third, it defines the profile as a set of topics of interest, each topic corresponding to a semantic cluster of keywords extracted by a specific clustering algorithm. Finally, the profile is represented according to the vector space model. The model is composed of several components organized in the form of a framework, in which we assessed the complexity of each component. The main components of the framework are: - a method for keyword queries disambiguation; - a method for semantically representing search query logs in the form of a taxonomy; - a clustering algorithm that allows fast and efficient identification of topics of interest as semantic clusters of keywords; - a method to identify user and data source profiles according to the generic model. This framework enables in particular to perform various tasks related to usage-based structuration of a distributed environment. As an example of application, the framework is used to the discovery of user communities, and the categorization of data sources. To validate the proposed framework, we conduct a series of experiments on real logs from the search engine AOL search, which demonstrate the efficiency of the disambiguation method in short queries, and show the relation between the quality based clustering and the structure based clustering

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Johansson, Ida, and Stina Johansson. "Users from a role perspective : A model to provide a user-centered system development process." Thesis, Linköping University, Department of Computer and Information Science, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8925.

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Today there exist several systems that lack usability. The reasons are, among others, the pressure to add more features in the system, but also that focus has been earlier on technology and functionality. It becomes more important to think of the user, so that systems can be more usable. By focusing on the user, the user experience can enhance, which results in more satisfied users.

User involvement in the system development process is one way to learn and receive information about the user. There are several ways of doing that. One way is to create user portraits from existing user models. We have studied different user models and lack a model that includes both tasks and goals; for example one of the existing models focus on user goals and another on relations with the system.

The purpose with this final thesis is to create a model to describe users as roles providing a more effective and generalized user-centered system development process.

To create this model, the role profile model, we studied existing theories. By them we were influenced both by good and less good things. The theoretical study resulted in a tentative model that we tested by interview and observe six buyers within the manufacturing industry. This resulted in two role profiles; the strategic buyer and purchase planner. From the result of the interviews and observations, we improved the tentative role profile model to our final model. There were some factors that did not fit in the tentative model and some that we added.

The role profile model contains three elements; objectives, requirements and context. These elements consist of a number of attributes that are important when surveying a role profile. The uniqueness with the role profile model is the fact that it includes both role specific attributes and attributes that puts the role profile into a context. The model contains for example work process, system requirements, responsibility and authority.

The role profile is at part of a greater context. There are design philosophies that concern the whole system development process; from survey the user to design and test. Our role profile model only handles the first parts, the user and tasks, due to the time limitations.

We have created a practical procedure that we recommend to facilitate the usage of the role profile model. The practical procedure is based on our choices of method when testing the tentative role profile model. The central in our practical procedure are interviews and observations. It is important to plan the company visits so that all necessary information is received.

The usage of the role profile can for example contribute with: knowledge and understanding of the users, structured work procedure, a generally accepted terminology and a user-centered design process.

This final thesis has been performed on commission of Lawson Software. We had continuously discussions with them about usability and the role profile model. We have studied fields of applications for the role profile model at Lawson. We think they can use the model in the product requirement process, design and evaluation, work with composite applications, user understanding and user priority and introduction of new employees.

Idag finns det ett flertal system som har bristande användar¬vänlighet. Detta beror bland annat på påtryckningar att lägga till fler funktioner i systemen, men också på att det bakåt i tiden har fokuserats på att utveckla system utifrån teknologi och funktionalitet. Det blir allt viktigare att tänka på användaren så att systemen blir mer användarvänliga. Genom att fokusera på användaren kan man öka användarupplevelsen i systemet och det medför att användarna blir nöjdare.

Att involvera användaren i utvecklingsprocessen är ett sätt att lära känna och få information om användaren. Det finns många sätt att göra det på. Ett sätt är att skapa användarporträtt med hjälp av olika befintliga användarmodeller. Vi har studerat olika användarmodeller och sett att det saknas en användarmodell som inkluderar både fokus på användarens arbetsprocess och dess mål; till exempel en av de existerande modellerna fokuserar på användarens mål och en annan på relationer med system.

Syftet med detta examensarbete är därför att skapa en modell som beskriver användare som roller, som bidrar till en effektivare och bredare användar¬centrerad systemutvecklingsprocess.

För att ta fram denna modell, rollprofilsmodellen, studerade vi som sagt existerande teorier. Från dem påverkades vi både av delar som vi tyckte var bra och mindre bra. Vi kom fram till en hypotesmodell som vi testade genom att intervjua och observera sex inköpare på tillverkande företag. Detta resulterade i två rollprofiler; den strategiska inköparen och inköpsplaneraren. Utifrån resultaten av intervjuerna och observationerna förbättrade vi hypotesen till vår slutliga modell. Det fanns vissa faktorer som vi inte tyckte passade in, men även attribut som borde läggas till.

Rollprofilsmodellen innehåller tre delar; mål, krav och kontext. Dessa delar består av ett antal attribut som är viktiga att undersöka hos den rollprofil som ska skapas. Det som utmärker rollprofilsmodellen är att den inkluderar både roll¬speci¬fika mål och attribut som sätter rollprofilen i en kontext. Modellen innehåller till exempel relationer, krav, ansvar och befogenheter.

Rollprofilen är en del av en större kontext. Det finns designfilosofier som berör hela systemutvecklingsprocessen; från att kartlägga användaren till att designa och testa. På grund av tidsbegränsningar har vi enbart berört de första av dessa delar; användaren och arbetsuppgifter.

För att underlätta användandet av rollprofilen har vi skapat ett rekommenderat praktiskt tillvägagångssätt. Detta är baserat på våra egna metodval när vi testade vår hypotesmodell. Det centrala i det praktiska tillvägagångssättet är intervjuer och observa¬tioner. Det är viktigt att planera noggrant så att all nödvändig informa¬tion erhålls.

Användandet av rollprofilen kan till exempel bidra till: kunskap och förståelse av användaren, ett strukturerat arbetssätt, en allmänt accepterad terminologi samt en användar¬centrerad utvecklingsprocess.

Detta examensarbete har utförts på uppdrag av Lawson Software, med vilka vi kontinuer¬ligt har fört diskussioner om användbarhet och rollprofilsmodellen med mera. Vi har även utforskat vilka potentiella användningsområden som rollprofilen har på Lawson. Lawson skulle kunna använda modellen i kravhanteringsprocessen, design och utvärdering, arbete med komposita applikationer, användarförståelse och priori¬teringar samt intro¬ducerande av nyanställda.

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Oelofse, Christina Hermiena. "The learner profile of a teenage cell phone user." Diss., Pretoria : [s.n.], 2009. http://upetd.up.ac.za/thesis/available/etd-07102009-160407.

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Kacem, Sahraoui Ameni. "Personalized information retrieval based on time-sensitive user profile." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30111/document.

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Les moteurs de recherche, largement utilisés dans différents domaines, sont devenus la principale source d'information pour de nombreux utilisateurs. Cependant, les Systèmes de Recherche d'Information (SRI) font face à de nouveaux défis liés à la croissance et à la diversité des données disponibles. Un SRI analyse la requête soumise par l'utilisateur et explore des collections de données de nature non structurée ou semi-structurée (par exemple : texte, image, vidéo, page Web, etc.) afin de fournir des résultats qui correspondent le mieux à son intention et ses intérêts. Afin d'atteindre cet objectif, au lieu de prendre en considération l'appariement requête-document uniquement, les SRI s'intéressent aussi au contexte de l'utilisateur. En effet, le profil utilisateur a été considéré dans la littérature comme l'élément contextuel le plus important permettant d'améliorer la pertinence de la recherche. Il est intégré dans le processus de recherche d'information afin d'améliorer l'expérience utilisateur en recherchant des informations spécifiques. Comme le facteur temps a gagné beaucoup d'importance ces dernières années, la dynamique temporelle est introduite pour étudier l'évolution du profil utilisateur qui consiste principalement à saisir les changements du comportement, des intérêts et des préférences de l'utilisateur en fonction du temps et à actualiser le profil en conséquence. Les travaux antérieurs ont distingué deux types de profils utilisateurs : les profils à court-terme et ceux à long-terme. Le premier type de profil est limité aux intérêts liés aux activités actuelles de l'utilisateur tandis que le second représente les intérêts persistants de l'utilisateur extraits de ses activités antérieures tout en excluant les intérêts récents. Toutefois, pour les utilisateurs qui ne sont pas très actifs dont les activités sont peu nombreuses et séparées dans le temps, le profil à court-terme peut éliminer des résultats pertinents qui sont davantage liés à leurs intérêts personnels. Pour les utilisateurs qui sont très actifs, l'agrégation des activités récentes sans ignorer les intérêts anciens serait très intéressante parce que ce type de profil est généralement en évolution au fil du temps. Contrairement à ces approches, nous proposons, dans cette thèse, un profil utilisateur générique et sensible au temps qui est implicitement construit comme un vecteur de termes pondérés afin de trouver un compromis en unifiant les intérêts récents et anciens. Les informations du profil utilisateur peuvent être extraites à partir de sources multiples. Parmi les méthodes les plus prometteuses, nous proposons d'utiliser, d'une part, l'historique de recherche, et d'autre part les médias sociaux
Recently, search engines have become the main source of information for many users and have been widely used in different fields. However, Information Retrieval Systems (IRS) face new challenges due to the growth and diversity of available data. An IRS analyses the query submitted by the user and explores collections of data with unstructured or semi-structured nature (e.g. text, image, video, Web page etc.) in order to deliver items that best match his/her intent and interests. In order to achieve this goal, we have moved from considering the query-document matching to consider the user context. In fact, the user profile has been considered, in the literature, as the most important contextual element which can improve the accuracy of the search. It is integrated in the process of information retrieval in order to improve the user experience while searching for specific information. As time factor has gained increasing importance in recent years, the temporal dynamics are introduced to study the user profile evolution that consists mainly in capturing the changes of the user behavior, interests and preferences, and updating the profile accordingly. Prior work used to discern short-term and long-term profiles. The first profile type is limited to interests related to the user's current activities while the second one represents user's persisting interests extracted from his prior activities excluding the current ones. However, for users who are not very active, the short-term profile can eliminate relevant results which are more related to their personal interests. This is because their activities are few and separated over time. For users who are very active, the aggregation of recent activities without ignoring the old interests would be very interesting because this kind of profile is usually changing over time. Unlike those approaches, we propose, in this thesis, a generic time-sensitive user profile that is implicitly constructed as a vector of weighted terms in order to find a trade-off by unifying both current and recurrent interests. User profile information can be extracted from multiple sources. Among the most promising ones, we propose to use, on the one hand, searching history. Data from searching history can be extracted implicitly without any effort from the user and includes issued queries, their corresponding results, reformulated queries and click-through data that has relevance feedback potential. On the other hand, the popularity of Social Media makes it as an invaluable source of data used by users to express, share and mark as favorite the content that interests them

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Nadee, Wanvimol. "Modelling user profiles for recommender systems." Thesis, Queensland University of Technology, 2016. https://eprints.qut.edu.au/93723/1/Wanvimol_Nadee_Thesis.pdf.

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Recommender systems assist users in finding what they want. The challenging issue is how to efficiently acquire user preferences or user information needs for building personalized recommender systems. This research explores the acquisition of user preferences using data taxonomy information to enhance personalized recommendations for alleviating cold-start problem. A concept hierarchy model is proposed, which provides a two-dimensional hierarchy for acquiring user preferences. The language model is also extended for the proposed hierarchy in order to generate an effective recommender algorithm. Both Amazon.com book and music datasets are used to evaluate the proposed approach, and the experimental results show that the proposed approach is promising.

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Mahmood, Omer. "ADAPTIVE PROFILE DRIVEN DATA CACHING AND PREFETCHING IN MOBILE ENVIRONMENT." Thesis, The University of Sydney, 2005. http://hdl.handle.net/2123/714.

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This thesis describes a new method of calculating data priority by using adaptive mobile user and device profiles which change with user location, time of the day, available networks and data access history. The profiles are used for data prefetching, selection of most suitable wireless network and cache management on the mobile device in order to optimally utilize the device's storage capacity and available bandwidth. Some of the inherent characteristics of mobile devices due to user movements are – non-persistent connection, limited bandwidth and storage capacity, changes in mobile device's geographical location and connection (eg. connection can be from GPRS to WLAN to Bluetooth). New research is being carried out in making mobile devices work more efficiently by reducing and/or eliminating their limitations. The focus of this research is to propose, evaluate and test a new user profiling technique which specifically caters to the needs of the mobile device users who are required to access large amounts of data, possibly more than the device storage capability during the course of the day or week. This work involves the development of an intelligent user profiling system along with mobile device caching system which will first allocate weight (priority) to the different sets and subsets of the total given data based on user's location, user's appointment information, user's preferences, device capabilities and available networks. Then the profile will automatically change the data weights with user movements, history of cached data access and characteristics of available networks. The Adaptive User and Device Profiles were designed to handle broad range of the issues associated with: •Changing network types and conditions •Limited storage capacity and document type support of mobile devices •Changes in user data needs due to their movements at different times of the day Many research areas have been addressed through this research but the primary focus has remained on the following four core areas. The four core areas are : selecting the most suitable wireless network; allocating weights to different datasets & subsets by integrating user's movements; previously accessed data; time of the day with user appointment information and device capabilities.

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Mahmood, Omer. "ADAPTIVE PROFILE DRIVEN DATA CACHING AND PREFETCHING IN MOBILE ENVIRONMENT." University of Sydney. Information Technologies, 2005. http://hdl.handle.net/2123/714.

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This thesis describes a new method of calculating data priority by using adaptive mobile user and device profiles which change with user location, time of the day, available networks and data access history. The profiles are used for data prefetching, selection of most suitable wireless network and cache management on the mobile device in order to optimally utilize the device�s storage capacity and available bandwidth. Some of the inherent characteristics of mobile devices due to user movements are �non-persistent connection, limited bandwidth and storage capacity, changes in mobile device�s geographical location and connection (eg. connection can be from GPRS to WLAN to Bluetooth). New research is being carried out in making mobile devices work more efficiently by reducing and/or eliminating their limitations. The focus of this research is to propose, evaluate and test a new user profiling technique which specifically caters to the needs of the mobile device users who are required to access large amounts of data, possibly more than the device storage capability during the course of the day or week. This work involves the development of an intelligent user profiling system along with mobile device caching system which will first allocate weight (priority) to the different sets and subsets of the total given data based on user�s location, user�s appointment information, user�s preferences, device capabilities and available networks. Then the profile will automatically change the data weights with user movements, history of cached data access and characteristics of available networks. The Adaptive User and Device Profiles were designed to handle broad range of the issues associated with: �Changing network types and conditions �Limited storage capacity and document type support of mobile devices �Changes in user data needs due to their movements at different times of the day Many research areas have been addressed through this research but the primary focus has remained on the following four core areas. The four core areas are : selecting the most suitable wireless network; allocating weights to different datasets & subsets by integrating user�s movements; previously accessed data; time of the day with user appointment information and device capabilities.

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Lal, Neeraj. "Enhancing Location-Based Content Delivery Through Semi-Automated Generation of User Profile." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1293731843.

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Chukala, Sileshi. "A Move Towards Practicability : Context Information and User Profile Management for the SensibleThings Platform." Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-29365.

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Achievements in academia and industry indicate a move towards the creation of a giant smart system including objects of different sizes, shapes, and purposes where the Internet will be so diverse and more resourceful with the incorporation of different smart devices. Mid Swe-den University took a first step towards providing an appropriate plat-form for Internet of Things applications known as SensibleThings for the emerging intercommunication of “objects”, called Internet of Things. The SensibleThings platform has produced components for sharing sensor-based context information on the Internet, in order to enable Internet of Things applications. In this thesis the plan was to contribute to filling the gap between the IoT and developers in academia as well as in the industries. The aim of the project was to create basic functionality to enable users to find new interesting users on the IoT and prioritize existing users. To this end context information and user profile man-agement is proposed and presented. Furthermore, a comparison be-tween the platform with the proposed extension as well as without was compared and examined.

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Silvestroni, Andrea. "NOEL - Applicativo Web di Residual Noise Extraction e User Profile Linking." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/17736/.

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In questo elaborato verranno illustrati il procedimento ed i risultati ottenuti in seguito allo sviluppo di un applicativo web, NOEL, nato per consentire l’interazione con uno studio di Smartphone Fingerprinting.

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Carimo, Rossana. "Evaluation of the UML profile for QoS from the user perspective." Thesis, Blekinge Tekniska Högskola, Avdelningen för programvarusystem, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5828.

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Addressing Quality of Service and specification of quality attributes has been gaining a growing importance in the software engineering area. The research presented in this study investigates different approaches to specification of Quality of Service. UML profile for Quality of Service is one of the standards of the Quality of Service specification and is described in the QoS specification context. The research aim of this thesis is the evaluation of the UML profile for Quality of Service against the following criteria: expressiveness, reusability, understandability, applicability and tool support, as well as further comparison of the profile with other Quality of Service specification languages. To perform that, several tasks and activities were conducted, such as a survey on different QoS specification languages, an examination of the UML profile for Quality of Service, the formulation of the evaluation criteria, and the appliance of the criteria in the evaluation and comparison processes. This study is performed from the perspective of readers and users of the profile that are not UML experts but have sufficient knowledge of UML in terms of software systems analysis and design. The context of the UML profile and Quality of Service aspects include basic concepts of the UML 2.0 and Quality of Service which will be described along the thesis. The main contribution of the thesis is the evaluation of the UML profile for Quality of Service against a set of criteria, followed by explanations on the contents of the profile and how Quality of Service is specified within it. The presented comparison of the UML profile and other Quality of Service specification languages could be the basis for a user to decide what language to use in a particular situation. This study can be comprehended as a starting point for further evaluation of the UML profile and its comparison with other quality specification languages.

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Al, Alshaikh Modhi. "Dynamic multi-concept user profile modelling in research paper recommender systems." Thesis, University of Brighton, 2018. https://research.brighton.ac.uk/en/studentTheses/8860a703-0d0b-49ef-aa00-ecece40d21d8.

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The internet and the digital libraries are major sources of information for researchers, and there is an enormous growth of information on these sources. A large number of research papers are available which leads to the information overload problem and hence finding research papers that are related to users’ interests become difficult and time consuming. The field of recommender systems aims to solve the information overload problem by filtering information and providing users with relevant results. Although the current recommender systems provide recommendation services to users, different limitations and challenges have not been adequately addressed in the research paper domain. The work presented in this thesis contributes to the development of models and algorithms to the recommender systems in the research paper domain. The main aim of this thesis is to develop a dynamic multiconcept system that is able to recommend research papers of interest at appropriate times. The first contribution of this thesis is modelling dynamic user profiles that are able to adapt to the changes in multiple user interests and to be compatible with the requirements of advanced ontologies. The second contribution is analysing users’ reading behaviour with research papers to develop novel short-term and long-term models that are able to adapt dynamically according to a user’s changing behaviour during his/her short and long term goals. These models can effectively learn different users’ reading behaviours implicitly without the need for any intervention from the user. The third contribution is predicting user’s future interests using a novel collaborative filtering approach without the need for the user ratings. All our proposed models are evaluated using offline evaluations with the BibSonomy dataset that contains actual users’ records. Our results show that our models outperform the baselines used for comparisons. Finally, we integrated our models to one unified dynamic hybrid system in order to provide recommendations which most closely represent the users’ research interests at particular times. The evaluation results indicate that the dynamic hybrid system that models and integrates multiple user interests and concepts can bring substantial benefits to a recommender system in the research paper domain.

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Carlsson, Anders, Simon Johansson, and Jacob Svedlund. "Roaming User Profiles : En undersökning av olika versioner och dess kompatibilitet." Thesis, Linnaeus University, School of Computer Science, Physics and Mathematics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-8256.

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När Windows Vista introducerades förändrades mappstrukturen för hur användarprofilen sparas jämfört med tidigare Windowsversioner såsom Windows XP. Denna rapport undersöker kompatibilitetsproblem med Roaming User Profiles mellan äldre och nyare versioner av operativsystemet. Syftet med rapporten var att utreda vilka problem som kan uppstå, vad det gäller Roaming User Profiles, vid en övergång från Windows XP till Windows Vista eller 7. Undersökningen genomfördes med hjälp av laborationer, litteratur och tester för att hitta problemen såväl som lösningar till dem. Resultatet visar att profiler skapade med Windows XP inte följer med till Windows Vista eller 7 utan det skapas sammanlagt två olika profiler, en för det äldre och en för det nyare operativsystemet. Ett skript som kopierar en användares filer från Windows XP till Vista/7 utformades därför. Slutligen presenterades en handlingsplan med olika alternativ vid en övergång från Windows XP till den nyare generationen av operativsystemen i Windowsfamiljen. Folder Redirection är en väl fungerande lösning dock går funktionaliteten som Roaming User Profiles erbjuder förlorad eftersom man endast får en uppmappning av bl.a. ”Mina Dokument” och ”Start Menu”.

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Limam, Lyes [Verfasser], Harald [Akademischer Betreuer] Kosch, and Lionel [Akademischer Betreuer] Brunie. "Usage-Driven Unified Model for User Profile and Data Source Profile Extraction / Lyes Limam. Betreuer: Harald Kosch ; Lionel Brunie." Passau : Universität Passau, 2015. http://d-nb.info/1074020979/34.

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Öknegård, Enavall Isabell, and Julia Mineur. "Privacy and user profiling : Profile-based evaluation of what different third party services may learn about a user." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177643.

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Online behavioural targeted advertising has become a leading method to increase theeffectiveness of advertisement online. The advertisement is based on information aboutusers’ internet activities collected by third party tracking services. However, there is a fineline between whether this should be considered a privacy leakage or an unharmful way toimprove the experience. This thesis presents a methodology for understanding and analyzing how significant personal information leakage to third parties is. To investigate theinformation leakage, a web crawler was implemented with the purpose to imitate fictiveusers browsing the web. The users’ activity online was based on the fictive user’s interestsand personal information. For every webpage visited, data such as text, URLs and screenshots were saved. The data were analyzed and the finding revealed that third parties generated targeted ads based on personal information regardless of the browser, user’s profile,and geographical location. However, we observed that targeted ads are a frequent practiceand noticed that categories valued more by advertisers are more intensely targeted.

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On-At, Sirinya. "Temporalité et réseaux sociaux : prise en compte de l'évolution dans la construction du profil utilisateur." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30071/document.

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Pour pouvoir restituer des informations qui correspondent aux besoins de l'utilisateur, les mécanismes d'adaptation doivent disposer de métadonnées sur celui-ci telles que ses caractéristiques personnelles, ses préférences générales, ses centres d'intérêt. De ce fait, le profil utilisateur construit à partir de celles-ci devient central dans tout système basé sur la personnalisation. Dans cette thèse, nous nous focalisons sur l'approche qui consiste à s'appuyer sur le réseau social de l'utilisateur pour enrichir le profil de cet utilisateur, les métadonnées explicites étant complétées par les informations issues de notre processus d'analyse. Nous appelons les techniques ou processus associés à cette approche " profilage social ". Le terme " profil social " désigne un profil construit à l'aide du réseau social de l'utilisateur. Un profil social contient les métadonnées traduisant les intérêts de l'utilisateur extraits à partir des informations partagées par les individus de son réseau social. Les intérêts de l'utilisateur évoluant au fil du temps dans la vie réelle, il en est de même pour ceux extraits depuis son réseau social : pertinents à un moment donné, ils peuvent ne plus être significatifs ultérieurement. Partant de ce constat, les principales informations que nous souhaitons étudier pour détecter un changement de centres d'intérêt ne sont pas ciblées sur l'utilisateur lui-même mais sur les éléments de son réseau social (liens entre les membres, informations qui circulent entre eux) : l'évolution du profil social de l'utilisateur est donc liée à l'évolution de son réseau social. Nous proposons une démarche générique de profilage social efficace permettant de construire un profil social représentatif de l'utilisateur prenant en compte différents types de réseaux ainsi que leurs caractéristiques évolutives. Pour prendre en compte l'évolution des intérêts dans le profil social, nous avons proposé d'améliorer l'efficacité des processus de construction du profil social existants en intégrant la prise en compte de l'évolution du réseau social de l'utilisateur. Nous proposons d'intégrer un facteur temporel dans ces processus (approche basée sur des individus et approche basée sur les communautés). La solution permet de privilégier les intérêts provenant d'informations significatives et à jour. Il s'agit donc d'intégrer une mesure temporelle dans l'étape d'extraction et pondération des intérêts. Cette mesure est calculée d'une part, à partir de la pertinence temporelle des informations utilisées pour extraire cet intérêt et d'autre part, à partir de la pertinence temporelle de l'individu qui partage ces informations. Nous mettons en œuvre la méthode proposée au travers d'expérimentations dans deux réseaux sociaux différents : DBLP, un réseau de publications scientifiques et Twitter, un réseau de micro-blogs. Les résultats de ces expérimentations nous ont permis de montrer l'efficacité de la méthode temporelle proposée par rapport aux processus de construction du profil social qui ne prennent pas en compte des critères temporels. En étudiant les résultats en fonction des techniques de pondération des intérêts ou fonctions temporelles utilisées, nous constatons que la fonction temporelle et la technique utilisées donnant les meilleurs résultats varient selon l'approche de construction du profil social choisie, selon la taille et la densité du réseau étudié mais aussi selon sur le type de réseau. La problématique abordée dans cette thèse est relativement nouvelle dans le contexte des systèmes de personnalisation de l'information et ouvre de nombreuses perspectives : évaluation du profil social dans un système de recommandation par exemple, application de la méthode proposée dans d'autres types de réseaux sociaux, application de techniques de mise à jour du profil, conception d'une plateforme de construction du profil social selon les caractéristiques du réseau
User profiling is essential for personalization systems (e.g. personalized information retrieval systems, recommendation systems) to identify user information (preference, interests...), in order to propose relevant content based on his/her specific needs and requirements. Many works have shown that user's social neighbors can be a meaningful source to infer his/her interests. Besides, sociology works have shown that the user is better described by people around him/her, especially the people that are directly connected to him/her (his egocentric network). In this work, the term "social profiling" is considered as the interest extraction approach that consists in extracting user interests from information of his/her social neighbors. The user's profile built within this approach is called "social profile". As user behaviors evolve over time, it is necessary to take into consideration the evolution of user interests in user profiling process. In the case of social profile, user interests are extracted from the information shared by his/her social neighbors. Hence, the evolution of extracted interests is related to the evolution of information shared on user social network and to the evolution of relationships between the user and his/her social neighbors. This issue becomes particularly important in the Online Social Networks (OSNs) context where user behavior changes quickly. For a user, the relationships and information in his/her social network can evolve and become obsolete for him/her overtime. Two users creating a relationship are not required to know each other in real life. Thus, the relationship persistence is not always maintained in this case. Social events or viral marketing (buzz) are also factors that enhance online social content sharing. In this work, we propose a generic approach that considers the evolution in user's social network in the social profiling process and can be applied in different types of social network. To handle this, we propose to apply a time-aware method into existing social profile building process (individual based and community based approaches). This strategy aims at weighting user's interests in the social profile based on their temporal score. The temporal score of an interest is computed by combining the temporal score of information used to extract the interests (computed by considering their freshness) with the temporal of individuals who share the information in the network (computed by considering the freshness of the interaction with the user). The technique and temporal function used to compute the temporal score are customizable. Thus, we can find out the most appropriate technique or temporal function depending on the types or characteristics of the adopted social network. The experiments conducted on DBLP and Twitter showed that the so-called time-aware social profiling process applying our proposed time-aware method outperforms the existing time-agnostic social profiling process. We also found that the most appropriate technique, temporal function and social profiling approach vary depending on the network characteristics (size, density) and to the social network type. Our approach opens many opportunities for future studies in social information filtering and many application domains as well as on the Web (e.g. evolution of social profile in personalization of search engines, recommender systems in e-commerce,). Our long-term perspective consists in the proposal of a generic platform that extracts the information and builds the user social profile based on the type and the specific characteristics of the underlying social network. Such a platform would be parameterized by the characteristics of the targeted social network using a machine learning approach

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Gao, Wei. "CONSTRUCTING USER BEHAVIORAL PROFILES USING DATA-MINING-BASED APPROACH." Diss., Tucson, Arizona : University of Arizona, 2005. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu%5Fetd%5F1261%5F1%5Fm.pdf&type=application/pdf.

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Ekblad, Alice, and Anna Höglund. "Profile-based comparison of user integrity and advertisement content when using different adblockers." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-178199.

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Advertisements are a common way to increase the revenue for websites. All users, however, are not interested in exposing themselves to advertisements and instead avoids it by installing an ad-blocker extension to their browser. In this thesis, a data collection followed by an analysis of the created dataset has been performed, with the purpose of identifying possible user integrity issues when using the ad-blocker extensions AdBlock and Adblock Plus. The study focuses on what kind of advertisements are displayed to a user and if it depend on the used ad-blocker extension or lack thereof, regional location, and the used browser. The data collection was carried out using a Selenium-based data collection tool, which both impersonated a real user surfing the Internet and scraped data from the visited websites along the way. The data collection was performed during a period of 21 days, using five different fictional users. A critical part of the thesis has been to find out how well user profiling, in the context of distributing targeted advertisement, works depending on if an ad-blocker extension is utilized or not. The used tool visited around 162 unique URLs per session and day, resulting in a dataset for further analysis. It was concluded that few differences in the number of targeted vs. untargeted ads a user was exposed to occurred in relation to regional location and used browser. The amount of advertisement decreased with the use of an ad-blocker, however, the data indicated that the share of targeted ads, compared to untargeted, increase with the use of an ad-blocker extension.

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Rouhi, Rahimeh <1986&gt. "Classification and Clustering of Shared Images on Social Networks and User Profile Linking." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amsdottorato.unibo.it/9403/1/Rahimeh_Rouhi_Thesis.pdf.

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The ever increasing prevalence of smartphones and the popularity of social network platforms have facilitated instant sharing of multimedia content through social networks. However, the ease in taking and sharing photos and videos through social networks also allows privacy-intrusive and illegal content to be widely distributed. As such, images captured and shared by users on their profiles are considered as significant digital evidence for social network data analysis. The Sensor Pattern Noise (SPN) caused by camera sensor imperfections during the manufacturing process mainly consists of the Photo-Response Non-Uniformity (PRNU) noise that can be extracted from taken images without hacking the device. It has been proven to be an effective and robust device fingerprint that can be used for different important digital image forensic tasks, such as image forgery detection, source device identification and device linking. Particularly, by fingerprinting the camera sources captured a set of shared images on social networks, User Profile Linking (UPL) can be performed on social network platforms. The aim of this thesis is to present effective and robust methods and algorithms for better fulfilling shared image analysis based on SPN. We propose clustering and classification based methods to achieve Smartphone Identification (SI) and UPL tasks, given a set of images captured by a known number of smartphones and shared on a set of known user profiles. The important outcome of the proposed methods is UPL across different social networks where the clustered images from one social network are applied to fingerprint the related smartphones and link user profiles on the other social network. Also, we propose two methods for large-scale image clustering of different types of the shared images by users, without prior knowledge about the types and number of the smartphones.

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Åberg, Maria. "Skill and knowledge matrix and evaluation tool for CAD-users at Atlas Copco Rock Drills AB." Thesis, Örebro University, School of Science and Technology, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-10017.

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Arhippainen, L. (Leena). "Studying user experience: issues and problems of mobile services:– Case ADAMOS: User experience (im)possible to catch?" Doctoral thesis, University of Oulu, 2009. http://urn.fi/urn:isbn:9789514291081.

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Abstract User experience has become a popular term in research and industry. There has been a great attempt to study and design user experiences. This thesis gives a practical view to user experience studies and methods by reporting test settings and results of the ADAMOS case studies. The goal of the ADAMOS project was to investigate context- and action-sensitive services in terms of how users experience when the system can detect one’s location and actions, and then adjust according to this information. The aim of this thesis is to investigate problems and issues in studying user experiences of mobile services and to find out in which conditions the study of user experience is possible and meaningful. As a contribution this thesis provides practical information for conducting user experience studies and evaluating experiences. The first contribution is a framework (U2E-Frame), which I created and improved iteratively in each test case. The framework is method-independent and it can be used for planning and conducting tests. The second contribution of the thesis is the practical view to all methods that are created, applied, presented and evaluated in this thesis. Especially during this thesis work three novel methods (Mobile Feedback, 3E-Diary and SUE methodology) have been developed and evaluated. The evaluation of the research methods illustrates that the best practice to study user experience is to use several methods together. This enables deeper understanding of user experiences. As the third contribution of this thesis I introduce a proposal of ten user experience heuristics for design and evaluation of user experiences. The aim of these heuristics is to enable designers to understand what meaning user experience has in product design. Developers can use these heuristics for designing and evaluating user experience aspects in product design. This thesis presents the main challenges in user experience research: know what to study (comprehensive user experience), know how to study it (find appropriate methods) and know how to evaluate and design it (user experience heuristics). An answer to the research problem is that it is both possible and meaningful to study user experience when we know user experience targets, and features of the services we want to investigate, and we can use the most appropriate methods, ensure the participant’s commitment to the test and ensure analysing relationships between results collected with different methods.

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Liang, Jian. "Information sharing in Onesocialweb using a multiple profile manager to better informed medical decision making processes." Thesis, Queensland University of Technology, 2011. https://eprints.qut.edu.au/49806/1/Jian_Liang_Thesis.pdf.

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The study shows an alternative solution to existing efforts at solving the problem of how to centrally manage and synchronise users’ Multiple Profiles (MP) across multiple discrete social networks. Most social network users hold more than one social network account and utilise them in different ways depending on the digital context (Iannella, 2009a). They may, for example, enjoy friendly chat on Facebook1, professional discussion on LinkedIn2, and health information exchange on PatientsLikeMe3 In this thesis the researcher proposes a framework for the management of a user’s multiple online social network profiles. A demonstrator, called Multiple Profile Manager (MPM), will be showcased to illustrate how effective the framework will be. The MPM will achieve the required profile management and synchronisation using a free, open, decentralized social networking platform (OSW) that was proposed by the Vodafone Group in 2010. The proposed MPM will enable a user to create and manage an integrated profile (IP) and share/synchronise this profile with all their social networks. The necessary protocols to support the prototype are also proposed by the researcher. The MPM protocol specification defines an Extensible Messaging and Presence Protocol (XMPP) extension for sharing vCard and social network accounts information between the MPM Server, MPM Client, and social network sites (SNSs). . Therefore many web users need to manage disparate profiles across many distributed online sources. Maintaining these profiles is cumbersome, time-consuming, inefficient, and may lead to lost opportunity. The writer of this thesis adopted a research approach and a number of use cases for the implementation of the project. The use cases were created to capture the functional requirements of the MPM and to describe the interactions between users and the MPM. In the research a development process was followed in establishing the prototype and related protocols. The use cases were subsequently used to illustrate the prototype via the screenshots taken of the MPM client interfaces. The use cases also played a role in evaluating the outcomes of the research such as the framework, prototype, and the related protocols. An innovative application of this project is in the area of public health informatics. The researcher utilised the prototype to examine how the framework might benefit patients and physicians. The framework can greatly enhance health information management for patients and more importantly offer a more comprehensive personal health overview of patients to physicians. This will give a more complete picture of the patient’s background than is currently available and will prove helpful in providing the right treatment. The MPM prototype and related protocols have a high application value as they can be integrated into the real OSW platform and so serve users in the modern digital world. They also provide online users with a real platform for centrally storing their complete profile data, efficiently managing their personal information, and moreover, synchronising the overall complete profile with each of their discrete profiles stored in their different social network sites.

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Dalmina, Leonardo. "GamiProM: a Gamification Model based on Profile Management." Universidade do Vale do Rio dos Sinos, 2018. http://www.repositorio.jesuita.org.br/handle/UNISINOS/7036.

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Submitted by JOSIANE SANTOS DE OLIVEIRA (josianeso) on 2018-05-07T13:43:19Z No. of bitstreams: 1 Leonardo Dalmina_.pdf: 3273879 bytes, checksum: df157a5701b423e92352934d75e44473 (MD5)
Made available in DSpace on 2018-05-07T13:43:19Z (GMT). No. of bitstreams: 1 Leonardo Dalmina_.pdf: 3273879 bytes, checksum: df157a5701b423e92352934d75e44473 (MD5) Previous issue date: 2018-03-26
CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
O uso de elementos de design de jogos em contextos não relacionados a jogos, definido como gamificação, está sendo cada vez mais usado para aumentar a motivação e o engajamento dos usuários quando eles precisam executar uma tarefa em um ambiente não relacionado a jogo, como o local de trabalho, a escola ou uma aplicação de software. No entanto, quando a gamificação precisa ser implementada, um desafio enfrentado pelos desenvolvedores é identificar quais elementos do jogos engajarão efetivamente os usuários de um software com base em seus perfis de usuário e características motivacionais. Frequentemente, muitas pesquisas tendem a não incluir ou apenas apoiar os tipos de usuário e fatores motivacionais mais comuns. Em resposta a este desafio, esta dissertação propõe um modelo de gamificação genérico intitulado GamiProM que permite um desenvolvedor de software criar uma solução gamificada adaptativa para qualquer área fazendo uso de ontologias e regras, visando fornecer representação do conhecimento bem como adicionar um valor semântico à informação gerada pela gamificação e gerenciamento de perfil. O modelo é avaliado com um teste de correlação que identifica a existência de qualquer associação entre as necessidades psicológicas básicas dos usuários e suas motivações coletadas com a aplicação gamificada, desenvolvida para implementar o modelo proposto. Os resultados mostraram que as motivações coletadas dos perfis gamificados dos usuários têm uma correlação acima de 80% com as necessidades psicológicas básicas analisadas.
The use of game design elements in non-game contexts, defined as gamification, is being increasingly used to raise the motivation and engagement of users when they have to execute a task in a non-game environment, such as the workplace, the school or a software application. However, when gamification needs to be implemented, a challenge faced by developers is to identify what game elements will effectively engage the users of a software based on their user profiles and motivational characteristics. Often, many researches tend to not include or only support the most common user types and motivational factors. In response to this challenge, this thesis proposes a generic gamification model entitled GamiProM that allows a software developer to build an adaptive gamified solution for any area by making use of ontologies and rules, aiming to provide knowledge representation as well as add a semantic value to the information generated by gamification and profile management. The model is evaluated with a correlation test that identifies the existence of any association between the basic psychological needs of the users and their motivations collected with the gamified application, developed to implement the proposed model. The results showed that the motivations collected from the gamified profiles of the users have a correlation above 80% with the basic psychological needs analyzed.

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Sutterer, Michael [Verfasser]. "User Profile Management and Selection in Context-Aware Service Platforms for Networks Beyond 3G / Michael Sutterer." Kassel : Universitätsbibliothek Kassel, 2009. http://d-nb.info/1000322289/34.

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Van, Schalkwyk Liesl-Dana. "The relationship between content providers and users in mobile television / Liesl-Dana van Schalkwyk." Thesis, North-West University, 2006. http://hdl.handle.net/10394/1267.

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Mobile television ( TV ) is a relatively new and unknown field of communication. Thus, role players in this field of communication find themselves in a new context for relationship. This raises the question as to what the key challenges in the relationship between content providers and users in mobile TV involve. More specifically, the following questions should be answered. Does mobile TV display particular characteristics of new media? If so, then how could content providers meet the challenge of understanding the user profile in mobile TV as a new medium? Also, how could content providers meet the challenge of adapting content provision according to the user experience of mobile TV as a new medium? This research paper explores these questions through means of an explorative literature study of relevant sources. Firstly, it provides a conceptual framework of mobile TV as well as an understanding of mobile TV within the greater context of new media. Secondly, it presents a means to understand the user profile in mobile N as a new medium. Lastly, it presents practical aspects that need to be considered when providing content for mobile TV as a new medium. The findings of the study can be summarised as follows: (a) Mobile TV portrays particular new media characteristics, such as, digitalisation, interactivity, hypertext, dispersal and virtuality. (b) A market-led approach should be employed in order to understand the user profile. (c) Mobile N content production should be integrated into the production process with the requirement that it is of a high quality and meets the technical and feasible limitations of the medium.
Thesis (M.A. (Communication Studies))--North-West University, Potchefstroom Campus, 2007.

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Rawat, Rakesh. "User behaviour modelling in a multi-dimensional environment for personalization and recommendation." Thesis, Queensland University of Technology, 2010. https://eprints.qut.edu.au/48135/1/Rakesh_Rawat_Thesis.pdf.

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Handling information overload online, from the user's point of view is a big challenge, especially when the number of websites is growing rapidly due to growth in e-commerce and other related activities. Personalization based on user needs is the key to solving the problem of information overload. Personalization methods help in identifying relevant information, which may be liked by a user. User profile and object profile are the important elements of a personalization system. When creating user and object profiles, most of the existing methods adopt two-dimensional similarity methods based on vector or matrix models in order to find inter-user and inter-object similarity. Moreover, for recommending similar objects to users, personalization systems use the users-users, items-items and users-items similarity measures. In most cases similarity measures such as Euclidian, Manhattan, cosine and many others based on vector or matrix methods are used to find the similarities. Web logs are high-dimensional datasets, consisting of multiple users, multiple searches with many attributes to each. Two-dimensional data analysis methods may often overlook latent relationships that may exist between users and items. In contrast to other studies, this thesis utilises tensors, the high-dimensional data models, to build user and object profiles and to find the inter-relationships between users-users and users-items. To create an improved personalized Web system, this thesis proposes to build three types of profiles: individual user, group users and object profiles utilising decomposition factors of tensor data models. A hybrid recommendation approach utilising group profiles (forming the basis of a collaborative filtering method) and object profiles (forming the basis of a content-based method) in conjunction with individual user profiles (forming the basis of a model based approach) is proposed for making effective recommendations. A tensor-based clustering method is proposed that utilises the outcomes of popular tensor decomposition techniques such as PARAFAC, Tucker and HOSVD to group similar instances. An individual user profile, showing the user's highest interest, is represented by the top dimension values, extracted from the component matrix obtained after tensor decomposition. A group profile, showing similar users and their highest interest, is built by clustering similar users based on tensor decomposed values. A group profile is represented by the top association rules (containing various unique object combinations) that are derived from the searches made by the users of the cluster. An object profile is created to represent similar objects clustered on the basis of their similarity of features. Depending on the category of a user (known, anonymous or frequent visitor to the website), any of the profiles or their combinations is used for making personalized recommendations. A ranking algorithm is also proposed that utilizes the personalized information to order and rank the recommendations. The proposed methodology is evaluated on data collected from a real life car website. Empirical analysis confirms the effectiveness of recommendations made by the proposed approach over other collaborative filtering and content-based recommendation approaches based on two-dimensional data analysis methods.

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Sewards, Sharon Kathleen. "To understand the current user profile of Leeds City Credit Union and examine the reasons for usage." Thesis, University of Leeds, 2011. http://etheses.whiterose.ac.uk/2405/.

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The aim of this thesis is to understand, using detailed modelling, the users and their reasons for use of Leeds City Credit Union (LCCU) with implied application for other UK credit unions. With the initial aims resulting from a Knowledge Transfer Programme (KTP) between LCCU and the University of Leeds, this study has been performed using a case-study (LCCU) with the intention that the findings can be adapted to suit the needs and understanding of other UK credit unions, thus answer the broader research questions around credit union usage. The original contribution to knowledge is therefore the modelling relating to the users and usage of LCCU so that a detailed understanding of the user profile can be tailored and applied to other UK credit unions as niche financial service providers. The main source of data for this thesis was the analysis of a user and non-user questionnaire and this was supported by the use of focus groups. This data was then analysed using a range of techniques: qualitative analysis through the focus groups; descriptive analysis; factor analysis; and regression. From this analysis it was discovered that users are motivated to join LCCU for three key reasons. There are those who: use providers offering the best rates of return; support the ethical stance that the credit union movement offers; and who are financially excluded and unable to access credit elsewhere. Each of these three segments displayed unique profiling characteristics. In addition responses between users and non-users were also compared to identify the significant characteristics of users. These findings were contrary to the expectation that credit unions are just for the poorest sectors of society. This provides not only a unique academic insight in this niche financial services provider but also practically, in the development of a marketing strategy as defined by the KTP programme.

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Bertmar, Sofia, and Johanna Gerhardsen. "Profile based evaluation of what different browsers and browser extensions may be able to learn about a user." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177163.

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Information leakage online has become a marketplace where companies can profile users to gain revenue from personalized advertising. This thesis offers a deeper analysis into what part the browsers Chrome and Firefox play in this targeted advertising. Privacy focused extensions have become a common way for users to avoid being exposed to third-party trackers, and two such extensions are Ghostery and CatBlock. By adding these to the browsers, this thesis examines how ads are affected during online sessions. Through development of a Selenium web crawler, several online profiles were built with the usage of personas based on specific interest categories. By performing daily sessions of Google search queries, data was collected in the form of ads and HTML text. The data collection lasted for a period of 21 days, using 29 virtual machines and 6 personas. This data was further used to analyze the extent of personalization of ads as profiles were built over time. The results obtained show similarities in how ads are targeted in the browsers, as well as the level of personalization that occurs when using an extension. Results show no major differences in level of targeting between the used browsers, but clearly show that a personalization of advertising has occurred. The usage of extensions proved to be efficient in reducing the amount of ads that a user is exposed to. However, the usage of extensions did not decrease the percentage of targeting amongst ads.

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Khemiri, Rym. "Vers l'OLAP collaboratif pour la recommandation des analyses en ligne personnalisées." Thesis, Lyon 2, 2015. http://www.theses.fr/2015LYO22015/document.

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La personnalisation vise à recueillir les intérêts, les préférences, les usages, les contraintes, le contexte, etc. souvent considérés comme faisant partie de ce que l'on appelle ''profil utilisateur'' pour ensuite les intégrer dans un système et les exploiter afin de permettre à l'utilisateur d'accéder rapidement aux informations les plus pertinentes pour lui. Par ailleurs, au sein d'une organisation, différents acteurs sont amenés à prendre des décisions à différents niveaux de responsabilité et ont donc besoin de réaliser des analyses à partir de l'entrepôt de données pour supporter la prise de décision. Ainsi, dans le contexte de cette communauté d'utilisateurs de l'entrepôt de données, la notion de collaboration émerge. Il est alors intéressant de combiner les concepts de personnalisation et de collaboration pour approcher au mieux les besoins des utilisateurs en leur recommandant des analyses en ligne pertinentes. L'objectif de ce mémoire est de proposer une approche collaborative pour l'OLAP, impliquant plusieurs utilisateurs, dirigée par un processus de personnalisation intégré aux systèmes décisionnels afin de pouvoir aider l'utilisateur final dans son processus d'analyse en ligne. Qu'il s'agisse de personnalisation du modèle d'entrepôt, de recommandation de requêtes décisionnelles ou de recommandation de chemins de navigation au sein des cubes de données, l'utilisateur a besoin d'un système décisionnel efficace qui l'aide dans sa démarche d'analyse en ligne. La finalité est de fournir à l'utilisateur des réponses pertinentes proches de ses besoins pour qu'il puisse mieux appréhender ses prises de décision. Nous nous sommes intéressés dans cette thèse à trois problèmes relevant de la prise en compte de l'utilisateur au sein des entrepôts de données et de l'OLAP. Nos contributions s'appuient sur la combinaison de techniques issues de la fouille de données avec les entrepôts et OLAP. Notre première contribution est une approche qui consiste à personnaliser les hiérarchies de dimensions afin d'obtenir des axes d'analyse nouveaux sémantiquement plus riches pouvant aider l'utilisateur à réaliser de nouvelles analyses non prévues par le modèle de l'entrepôt initial. En effet, nous relâchons la contrainte du modèle fixe de l'entrepôt, ce qui permet à l'utilisateur de créer de nouveaux axes d'analyse pertinents en tenant compte à la fois de ses contraintes et des connaissances enfouies dans les données entreposées. Notre approche repose sur une méthode d'apprentissage non-supervisé, le k-means contraint, capable de créer de nouveaux regroupements intéressants des données entreposées pouvant constituer un nouveau niveau de hiérarchie permettant de réaliser de nouvelles requêtes décisionnelles. L'intérêt est alors de pouvoir exploiter ces nouveaux niveaux de hiérarchie pour que les autres utilisateurs appartenant à la même communauté d'utilisateurs puissent en tirer profit, dans l'esprit d'un système collaboratif dans lequel chacun apporte sa pierre à l'édifice. Notre deuxième contribution est une approche interactive pour aider l'utilisateur à formuler de nouvelles requêtes décisionnelles pour construire des cubes OLAP pertinents en s'appuyant sur ses requêtes décisionnelles passées, ce qui lui permet d'anticiper sur ses besoins d'analyse futurs. Cette approche repose sur l'extraction des motifs fréquents à partir d'une charge de requêtes associée à un ou à un ensemble d'utilisateurs appartenant à la même communauté d'acteurs d'une organisation. Notre intuition est que la pertinence d'une requête décisionnelle est fortement corrélée avec la fréquence d'utilisation par l'utilisateur (ou un ensemble d'utilisateurs) des attributs associés à l'ensemble de ses (leurs) requêtes précédentes. Notre approche de formulation de requêtes (...)
The objective of this thesis is to provide a collaborative approach to the OLAP involving several users, led by an integrated personalization process in decision-making systems in order to help the end user in their analysis process. Whether personalizing the warehouse model, recommending decision queries or recommending navigation paths within the data cubes, the user need an efficient decision-making system that assist him. We were interested in three issues falling within data warehouse and OLAP personalization offering three major contributions. Our contributions are based on a combination of datamining techniques with data warehouses and OLAP technology. Our first contribution is an approach about personalizing dimension hierarchies to obtain new analytical axes semantically richer for the user that can help him to realize new analyzes not provided by the original data warehouse model. Indeed, we relax the constraint of the fixed model of the data warehouse which allows the user to create new relevant analysis axes taking into account both his/her constraints and his/her requirements. Our approach is based on an unsupervised learning method, the constrained k-means. Our goal is then to recommend these new hierarchy levels to other users of the same user community, in the spirit of a collaborative system in which each individual brings his contribution. The second contribution is an interactive approach to help the user to formulate new decision queries to build relevant OLAP cubes based on its past decision queries, allowing it to anticipate its future analysis needs. This approach is based on the extraction of frequent itemsets from a query load associated with one or a set of users belonging to the same actors in a community organization. Our intuition is that the relevance of a decision query is strongly correlated to the usage frequency of the corresponding attributes within a given workload of a user (or group of users). Indeed, our approach of decision queries formulation is a collaborative approach because it allows the user to formulate relevant queries, step by step, from the most commonly used attributes by all actors of the user community. Our third contribution is a navigation paths recommendation approach within OLAP cubes. Users are often left to themselves and are not guided in their navigation process. To overcome this problem, we develop a user-centered approach that suggests the user navigation guidance. Indeed, we guide the user to go to the most interesting facts in OLAP cubes telling him the most relevant navigation paths for him. This approach is based on Markov chains that predict the next analysis query from the only current query. This work is part of a collaborative approach because transition probabilities from one query to another in the cuboids lattice (OLAP cube) is calculated by taking into account all analysis queries of all users belonging to the same community. To validate our proposals, we present a support system user-centered decision which comes in two subsystems: (1) content personalization and (2) recommendation of decision queries and navigation paths. We also conducted experiments that showed the effectiveness of our analysis online user centered approaches using quality measures such as recall and precision

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Sulieman, Dalia. "Towards Semantic-Social Recommender Systems." Phd thesis, Université de Cergy Pontoise, 2014. http://tel.archives-ouvertes.fr/tel-01017586.

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In this thesis we propose semantic-social recommendation algorithms, that recommend an input item to users connected by a collaboration social network. These algorithms use two types of information: semantic information and social information.The semantic information is based on the semantic relevancy between users and the input item; while the social information is based on the users position and their type and quality of connections in the collaboration social network. Finally, we use depth-first search and breath-first search strategies to explore the graph.Using the semantic information and the social information, in the recommender system, helps us to partially explore the social network, which leads us to reduce the size of the explored data and to minimize the graph searching time.We apply our algorithms on real datasets: MovieLens and Amazon, and we compare the accuracy an the performance of our algorithms with the classical recommendation algorithms, mainly item-based collaborative filtering and hybrid recommendation.Our results show a satisfying accuracy values, and a very significant performance in execution time and in the size of explored data, compared to the classical recommendation algorithms.In fact, the importance of our algorithms relies on the fact that these algorithms explore a very small part of the graph, instead of exploring all the graph as the classical searching methods, and still give a good accuracy compared to the other classical recommendation algorithms. So, minimizing the size of searched data does not badly influence the accuracy of the results.

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Saffar, Illyyne. "Machine learning to infer user behavior in 5G autonomic networks." Thesis, Rennes 1, 2020. http://www.theses.fr/2020REN1S039.

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L'idée développée dans cette thèse est d’utiliser le Machine Learning Deep Learning et l’analyse de données radio 3GPP pour estimer et prédire le comportement d'un utilisateur, en termes d'habitudes et de préférence d'usage des services mobiles d’un réseau 5G. Le caractère multidimensionnel du comportement de l'utilisateur rend son estimation complexe et reste actuellement un défi. On a donc étudié son estimation sous une approche innovante au regard de l'état de l'art. On a proposé de la réaliser au sein d'un système unifié qui estime en parallèle chaque dimension du comportement. En utilisant des méthodes basées sur l’apprentissage approfondi (deep learning) supervisé et hybride/semi-supervisé, on propose une solution pour la détection de l’environnement (Indoor/ Outdoor Detection (IOD)) et jusqu'à 8 classes d'environnement d’un utilisateur de téléphone portable. Nous proposons ensuite une solution permettant de détecter la catégorie de mobilité (Mobility Speed Profile (MSP) Detection) jusqu'à 8 profils de vitesses. Enfin, une solution innovante basée sur des algorithmes d’apprentissage profond dans une architecture multitâches permet d'estimer conjointement à la fois l'environnement et le profil de mobilité. La comparaison avec l'état de l'art a montré l'efficacité des méthodes proposées. Ce qui permet d'envisager leur utilisation par des opérateurs mobiles au sein de leurs futurs
The main idea of this thesis is to use machine learning/deep learning techniques to estimate and predict user behavior by analyzing 3GPP radio signals. The user behavior is defined in terms of habits and preferences while consuming 5G services. The estimation of user behavior is complex and remains a challenge due to its multidimensional nature. We therefore studied an innovative approach for the user behavior estimation: we use a unified system which jointly as well as parallelly estimates each dimension of behavior. Using methods based on supervised and hybrid / semi-supervised deep-learning, we propose a solution for the detection of the user environment (from Indoor/ Outdoor Detection (IOD) to up to 8 classes). We then propose a solution to detect the mobility categories (Mobility Speed Profile (MSP) Detection) up to 8 speed profiles. Finally, an innovative solution jointly estimates both the environment and the mobility profile using deep learning algorithms and a multitasking architecture. The comparison with the state of the art shows the effectiveness of the proposed methods. This allows to consider its deployment by operators in future

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Asfari, Ounas. "Personalized Access to Contextual Information by using an Assistant for Query Reformulation." Thesis, Paris 11, 2011. http://www.theses.fr/2011PA112126.

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Les travaux présentés dans cette thèse rentrent dans le cadre de la Recherche d'Information (RI) et s'intéressent à une des questions de recherche actuellement en vogue dans ce domaine: la prise en compte du contexte de l'utilisateur pendant sa quête de l'information pertinente. Nous proposons une approche originale de reformulation automatique de requêtes basée sur le profil utilisateur et sa tâche actuelle. Plus précisément, notre approche tient compte deux éléments du contexte, les centres d'intérêts de l'utilisateur (son profil) et la tâche qu'il réalise, pour suggérer des requêtes appropriées à son contexte. Nous proposons, en particulier, toute une démarche originale permettant de bien interpréter et réécrire la requête initiale en fonction des activités réalisées dans la tâche courante de l'utilisateur.Nous considérons qu'une tâche est jalonnée par des activités, nous proposons alors d'interpréter le besoin de l'utilisateur, représenté initialement par la requête, selon ses activités actuelles dans la tâche (et son profil) et de suggérer des reformulations de requêtes appropriées à ces activités.Une implémentation de cette approche est faite, et elle est suivie d’une étude expérimentale. Nous proposons également une procédure d'évaluation qui tient compte l'évaluation des termes d'expansion, et l'évaluation des résultats retournés en utilisant les requêtes reformulées, appelés SRQ State Reformulated Query. Donc, trois facteurs d’évaluation sont proposés sur lesquels nous nous appuierons pour l'analyse et l'évaluation des résultats. L’objective est de quantifier l'amélioration apportée par notre système dans certains contextes par rapport aux autres systèmes. Nous prouvons que notre approche qui prend en compte la tâche actuelle de l'utilisateur est effectivement plus performante que les approches basées, soit uniquement sur la requête initiale, ou encore celle basée sur la requête reformulée en considérant uniquement le profil de l'utilisateur
Access to relevant information adapted to the needs and the context of the user is areal challenge in Web Search, owing to the increases of heterogeneous resources andthe varied data on the web. There are always certain needs behind the user query,these queries are often ambiguous and shortened, and thus we need to handle thesequeries intelligently to satisfy the user’s needs. For improving user query processing,we present a context-based hybrid method for query expansion that automaticallygenerates new reformulated queries in order to guide the information retrieval systemto provide context-based personalized results depending on the user profile andhis/her context. Here, we consider the user context as the actual state of the task thatthe user is undertaking when the information retrieval process takes place. Thus StateReformulated Queries (SRQ) are generated according to the task states and the userprofile which is constructed by considering related concepts from existing concepts ina domain ontology. Using a task model, we will show that it is possible to determinethe user’s current task automatically. We present an experimental study in order toquantify the improvement provided by our system compared to the direct querying ofa search engine without reformulation, or compared to the personalized reformulationbased on a user profile only. The Preliminary results have proved the relevance of ourapproach in certain contexts

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Chamsi, Abu Quba Rana. "On enhancing recommender systems by utilizing general social networks combined with users goals and contextual awareness." Thesis, Lyon 1, 2015. http://www.theses.fr/2015LYO10061/document.

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Nous sommes amenés chaque jour à prendre un nombre important de décisions : quel nouveau livre lire ? Quel film regarder ce soir ou où aller ce week-end ? De plus en plus, nous utilisons les ressources en ligne pour nous aider à prendre des décisions. Comme la prise de décision est assistée par le domaine en ligne, l'utilisation de systèmes de recommandation est devenue essentielle dans la vie quotidienne. Dans le même temps, les réseaux sociaux sont devenus une partie indispensable de ce processus ; partout dans le monde on les utilise quotidiennement pour récupérer des données de personne et de sources d'information en qui on a confiance. Quand les internautes passent du temps sur les réseaux sociaux, ils laissent de précieuses informations sur eux-mêmes. Cela a attiré l'attention des chercheurs et les professionnels de nombreux domaines académiques et commerciaux. Comme le domaine de la recommandation est un domaine qui a assisté à des changements de grande ampleur attribuable à des réseaux sociaux, il y a un intérêt évident pour les systèmes de recommandation sociale. Cependant, dans la littérature de ce domaine, nous avons constaté que de nombreux systèmes de recommandation sociale ont été évalués en utilisant des réseaux sociaux spécialisés comme Epinions, Flixter et d'autres types des réseaux sociaux de recommandation, qui tendent à être composées d'utilisateurs, d'articles, de notes et de relations. Ces solutions ne peuvent pas être étendues directement à des réseaux sociaux à usage général (GPSNs) comme Facebook et Twitter, qui sont des réseaux sociaux ouverts où les utilisateurs peuvent réaliser une variété d'actions utiles pour l'aide à la recommandation
We are surrounded by decisions to take, what book to read next? What film to watch this night and in the week-end? As the number of items became tremendous the use of recommendation systems became essential in daily life. At the same time social network become indispensable in people’s daily lives; people from different countries and age groups use them on a daily basis. While people are spending time on social networks, they are leaving valuable information about them attracting researchers’ attention. Recommendation is one domain that has been affected by the social networks widespread; the result is the social recommenders’ studies. However, in the literature we’ve found that most of the social recommenders were evaluated over Epinions, flixter and other type of domains based recommender social networks, which are composed of (users, items, ratings and relations). The proposed solutions can’t be extended directly to General Purpose Social Networks (GPSN) like Facebook and Twitter which are open social networks where users can do a variety of useful actions that can be useful for recommendation, but as they can’t rate items, these information are not possible to be used in recommender systems! Moreover, evaluations are based on the known metrics like MAE, and RMSE. This can’t guarantee the satisfaction of users, neither the good quality of recommendation

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Tebri, Hamid. "Formalisation et spécification d'un système de filtrage incrémental d'information." Toulouse 3, 2004. http://www.theses.fr/2004TOU30226.

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Le contexte d'étude de cette thèse est "les systèmes de filtrage d'Information (SFI)". Un SFI permet d'extraire, à partir d'un flot d'informations, celles qui sont susceptibles de répondre aux besoins de l'utilisateur appelés profils. D'une façon générale, à chaque arrivée d'un document, un score de similarité entre celui-ci et le profil est calculé. Une fonction de décision permet ensuite de décider d'accepter ou de rejeter ce document. Notre contribution se situe dans l'apprentissage des profils et l'adaptation de la fonction de décision. L'apprentissage du profil consiste à construire pour chaque document pertinent sélectionné un profil temporaire permettant de retrouver ce document avec un score fort. Ce profil temporaire est ensuite intégré dans le profil de l'utilisateur. L'adaptation de la fonction de décision consiste à estimer les probabilités des scores et de tracer leur distribution par une régression linéaire. Ensuite, de déduire le seuil qui permet d'optimiser une fonction d'utilité. Des expérimentations ont été présentées pour valider les méthodes proposées
The context of this thesis work is information filtering systems. Information filtering monitors a stream of incoming documents to find those that match the user's information need called profile. Usually, in order to identify whether a document is relevant or not a score that measures the similarity between a document and a profile is computed. When the score is higher than the threshold the document is selected, otherwise it is rejected. Our contribution is profiles learning and the decision function adaptation. The profile learning consists in constructing at each arrival of relevant document, a temporary profile allowing to reselect the document of interest with the highest score. Afterward, This temporary profile, is integrated in the profile of the user. The decision function adaptation consists to estimate the scores discrete probabilities, then plot the scores distribution using a linear regression. After that, deduce the threshold that permits to optimize this function. The experiments are presented to validate the proposed methods. Keywords: incremental filtering, user profile, temporary profile, reinforcement score, profile learning, adpating decision function, probabilities distribution

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Pereira, Matheus. "Representação semântica de perfil dinâmico de usuários em comunidades de prática." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2017. http://hdl.handle.net/10183/177588.

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Em comunidades de prática, a aprendizagem ocorre por meio da interação e colaboração constante de seus participantes, o caráter social destes ambientes é fundamental para a construção do conhecimento. Por este motivo, esta dissertação busca compreender a forma como os usuários interagem em comunidades de prática e propõe a estruturação destas informações em torno de um perfil dinâmico de usuário. A aplicação de perfis de usuário neste contexto permite entender o indivíduo, seus interesses e necessidades. A partir da representação dos participantes de comunidades de prática é possível desenvolver sistemas de aprendizagem inteligente, sistemas de recomendação, elementos de gamificação e sistemas de acesso e recuperação de informação personalizados. Estes mecanismos procuram estimular o engajamento dos participantes e promover a aprendizagem colaborativa. A representação das informações neste trabalho será apoiada pelo uso de tecnologias da web semântica e de ontologias para a formalização das relações em comunidades de prática. O desenvolvimento de softwares educacionais baseados na web semântica amplia a capacidade de implementação de novos mecanismos de aprendizagem, contribuindo para a análise das interações e a inferências sobre as informações dos usuários. O uso de ontologias permite a formalização das informações e torna possível a elaboração de uma rede de conhecimento que pode ser processada e consumida por agentes de software, contribuindo para a interoperabilidade do sistema.
In communities of practice, learning is built through constant interaction and collaboration of their participants, the social aspect of these environments is crucial for the knowledge construction. For this reason, this work intends to understand how users interact in communities of practice and proposes a dynamic user profile to structure this information. An user profile applied in this context allows us to understand the person, his interests and needs. The representation of participants in communities of practice allow us to develop intelligent learning systems, recommender systems, gamification elements and systems for personalized access and personalized information retrieval. Those mechanisms intend to stimulate participant engagement to promote collaborative learning. In this work, semantic web technologies and ontologies are used to represent this informations. The development of educational software based on the semantic web expands the capacity to implement new learning mechanisms, contributing to the analysis of the interactions and the inferences about user informations. The use of ontologies allows the formalization of information and enables the elaboration of a knowledge network that can be processed and consumed by software agents, contributing to the system interoperability.

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Coelho, Andreia Cristina Murteira. "Geração linkedln connection: análise do perfil e das motivações dos utilizadores." Master's thesis, Universidade de Évora, 2017. http://hdl.handle.net/10174/20969.

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O LinkedIn é uma ferramenta que veio alterar as técnicas tradicionais de recrutamento e seleção em recursos humanos, uma vez que permite aliar o conteúdo do cv, com o seu perfil online, tendo em conta as características pessoais, profissionais, sociais, bem como, as partilhas e publicações que tornem o perfil atrativo junto da entidade recrutadora. O objetivo geral da investigação consiste em analisar o perfil dos utilizadores do LinkedIn, como também, compreender as principais motivações da utilização desta rede social, tendo em vista uma determinada amostra de utilizadores da rede. Os objetivos específicos pretendem analisar detalhadamente esta situação, uma vez que vão identificar o perfil dos utilizadores do LinkedIn presente na rede social, compreender as motivações da participação dos utilizadores e conhecer as desvantagens na utilização do LinkedIn como ferramenta de recrutamento, como tal, optamos por uma abordagem quantitativa através da elaboração de um questionário, surgindo uma amostra com 185 respostas. A investigação envolve diferentes tipos de análise de forma a aprofundar a temática, pelo que dividimos a análise em quadro blocos fundamentais, primeiramente efetuamos uma análise descritiva, uma análise de clusters, seguida de uma análise discriminante, posteriormente enriquecida com a análise de uma entrevista a um especialista no LinkedIn. Os resultados obtidos salientam a existência de dois clusters com características muito homogéneas, todavia é possível verificar que o primeiro assume uma maior propensão para a partilha, ao passo que o segundo não atribui tanta relevância à partilha por privilegiar a sua privacidade; LinkedIn Connection Generation - Analysis of user profile and motivations Abstract: LinkedIn is a tool that has changed the traditional techniques of recruitment and selection of human resources, since it allows to combine the content of cv with your online profile, taking into account the personal characteristics, professional, social, as well as the shares and publications that make attractive profile with the recruiter entity. The possibilities that the network offers entice placement profiles, however, the motivations of users can be numerous, as such, it is essential to understand this phenomenon. The overall objective of the research analyzes the profile and motivation of LinkedIn users, but also understands the main motivations of using this social network with a view to a particular network users sample. The specific objectives aim to deeply analyze this situation as it will identify the LinkedIn profile users of this social network, understand the motivations of the involvement of users and know the disadvantages of using LinkedIn as a tool for recruitment, as such, we chose a quantitative approach by developing a questionnaire, emerging a sample of 185 respondents. The research involves different types of analysis in order to deepen the thematic, so we divided the analysis into a framework of fundamental blocks, first we performed a descriptive analysis, a cluster analysis, followed by a discriminant analysis, later enriched with the analysis of an interview A LinkedIn SpecialistThe results obtained highlight the existence of two clusters with very homogeneous characteristics, but it is possible to verify that the former assumes a greater pretense for sharing, while the latter devalues the sharing in favor of privacy.

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OPERTI, VALERIO. "Travellers¿ Preferences and Attitudes to understand Travel Behaviour and define Market Segmentation." Doctoral thesis, Politecnico di Torino, 2019. http://hdl.handle.net/11583/2739920.

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Olsén, Emma. "Redesign of a website and visual brand language : Development of a new website and graphic profile for an energy efficiency company." Thesis, Luleå tekniska universitet, Institutionen för ekonomi, teknik, konst och samhälle, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-83074.

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The project that is presented in this report is the result of a master thesis for the Industrial Design Engineering programme at Luleå University of Technology. The project was conducted towards and together with the company Leosol during the fall of 2020. For the past couple of years, Leosol has invested time and money into online advertisement. Their advertisement generates a greater visit flow onto their website; however, it rarely produces any bookings of their services. Leosol wants to increase the number of bookings done through their website. This master thesis is conducted to contribute towards Leosol’s goal regarding the online bookings. Therefore, the focus of this project has been to strengthen Leosol’s brand by exploring options for a new graphic profile and a visual brand language. These brand tools were be implemented in a new website. To achieve this, an altered version of IDEO’s Human-Centered Design process was implemented. By working close to the user, in this case, Leosol’s clients, the current issues and solutions was clarified. Throughout the process, the graphic profile and the wireframe was developed separately. In the last phase of the project, the two was combined into the final concept. The project resulted in a repositioning of Leosol’s brand, creating a new, more professional tone. The graphic profile was summarized through a poster, describing the new logotype, colours, fonts, imagery and a short description of how to apply them. This new graphic profile was applied onto the new wireframe, creating the final website. The layout of the website was developed so that the user can quickly identify Leosol’s identity and mission. By implementing a website that truly represents Leosol, there is a bigger chance that the number of bookings increase.
Projektet som presenteras i den här rapporten är resultatet av ett examensarbete för Civilingenjörslinjen Teknisk Design vid Luleå Tekniska Universitet. Projektet har drivits mot och i samarbete med energiföretaget Leosol under hösten 2020. Leosol har investerat både pengar och tid i annonsering online. Detta har genererat ett större besöksflöde, dock har det inte lett till en ökning av bokningar av deras tjänster. Leosol vill öka antalet bokningar som sker via deras hemsida. Detta examensarbete har utförts för att bidra till detta mål. Projektet har därför kretsat kring att förstärka Leosols varumärke genom att utforska olika alternativ till en ny grafisk profil och ett nytt visuellt varumärke. Dessa nya varumärkesverktyg kommer sedan att implementeras i en helt ny hemsida. En variant av IDEO’s Human-Centered Designprocess har använts under projektet för att uppnå detta. Genom att arbeta nära och tillsammans med användaren, i detta fall Leosols kunder, har de nuvarande problemen samt olika lösningar förtydligats och identifierats. Under processen har den grafiska profilen och wireframen för hemsidan skapats separat. I sista fasen i projektet kombinerades dessa till det slutgiltiga konceptet. Projektet har resulterat i en ompositionering av Leosols varumärke genom att skapa en mer professionell ton. Den grafiska profilen har sammanfattats i form av en poster. Denna beskriver den nya logotypen, färger, typsnitt, bildspråk samt en kort instruktion som förklarar hur dessa bör appliceras. Den nya grafiska profilen applicerades sedan på wireframen, för att skapa den slutgiltiga hemsidan. Hemsidans layout är skapad för att användaren ska snabbt kunna identifiera Leosol’s identitet samt deras tjänster. Genom att implementera en hemsida som verkligen representerar Leosol ökar chanserna för att antalet bokningar på deras hemsida stiger.

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Ben, Ticha Sonia. "Recommandation personnalisée hybride." Thesis, Université de Lorraine, 2015. http://www.theses.fr/2015LORR0168/document.

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Face à la surabondance des ressources et de l'information sur le net, l'accès aux ressources pertinentes devient une tâche fastidieuse pour les usagers de la toile. Les systèmes de recommandation personnalisée comptent parmi les principales solutions qui assistent l'utilisateur en filtrant les ressources, pour ne lui proposer que celles susceptibles de l’intéresser. L’approche basée sur l’observation du comportement de l’utilisateur à partir de ses interactions avec le e-services est appelée analyse des usages. Le filtrage collaboratif et le filtrage basé sur le contenu sont les principales techniques de recommandations personnalisées. Le filtrage collaboratif exploite uniquement les données issues de l’analyse des usages alors que le filtrage basé sur le contenu utilise en plus les données décrivant le contenu des ressources. Un système de recommandation hybride combine les deux techniques de recommandation. L'objectif de cette thèse est de proposer une nouvelle technique d'hybridation en étudiant les bénéfices de l'exploitation combinée d'une part, des informations sémantiques des ressources à recommander, avec d'autre part, le filtrage collaboratif. Plusieurs approches ont été proposées pour l'apprentissage d'un nouveau profil utilisateur inférant ses préférences pour l’information sémantique décrivant les ressources. Pour chaque approche proposée, nous traitons le problème du manque de la densité des données et le problème du passage à l’échelle. Nous montrons également, de façon empirique, un gain au niveau de la précision des recommandations par rapport à des approches purement collaboratives ou purement basées sur le contenu
Face to the ongoing rapid expansion of the Internet, user requires help to access to items that may interest her or him. A personalized recommender system filters relevant items from huge catalogue to particular user by observing his or her behavior. The approach based on observing user behavior from his interactions with the website is called usage analysis. Collaborative Filtering and Content-Based filtering are the most widely used techniques in personalized recommender system. Collaborative filtering uses only data from usage analysis to build user profile, while content-based filtering relies in addition on semantic information of items. Hybrid approach is another important technique, which combines collaborative and content-based methods to provide recommendations. The aim of this thesis is to present a new hybridization approach that takes into account the semantic information of items to enhance collaborative recommendations. Several approaches have been proposed for learning a new user profile inferring preferences for semantic information describing items. For each proposed approach, we address the sparsity and the scalability problems. We prove also, empirically, an improvement in recommendations accuracy against collaborative filtering and content-based filtering

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Kirmemis, Oznur. "Openmore: A Content-based Movie Recommendation System." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609479/index.pdf.

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The tremendous growth of Web has made information overload problem increasingly serious. Users are often confused by huge amount of information available on the internet and they are faced with the problem of finding the most relevant information that meets their needs. Recommender systems have proven to be an important solution approach to this problem. This thesis will present OPENMORE, a movie recommendation system, which is primarily based on content-based filtering technique. The distinctive point of this study lies in the methodology used to construct and update user and item profiles and the optimizations used to fine-tune the constructed user models. The proposed system arranges movie content data as features of a set of dimension slots, where each feature is assigned a stable feature weight regardless of individual movies. These feature weights and the explicit feedbacks provided by the user are then used to construct the user profile, which is fine-tuned through a set of optimization mechanisms. Users are enabled to view their profile, update them and create multiple contexts where they can provide negative and positive feedback for the movies on the feature level.

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Noël, Romain. "Contribution à la veille stratégique : DOWSER, un système de découverte de sources Web d’intérêt opérationnel." Thesis, Rouen, INSA, 2014. http://www.theses.fr/2014ISAM0011/document.

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L'augmentation constante du volume d'information disponible sur le Web a rendu compliquée la découverte de nouvelles sources d'intérêt sur un sujet donné. Les experts du renseignement doivent faire face à cette problématique lorsqu'ils recherchent des pages sur des sujets spécifiques et sensibles. Ces pages non populaires sont souvent mal indexées ou non indexées par les moteurs de recherche à cause de leur contenu délicat, les rendant difficile à trouver. Nos travaux, qui s'inscrivent dans ce contenu du Renseignement d'Origine Source Ouverte (ROSO), visent à aider l'expert du renseignement dans sa tâche de découverte de nouvelles sources. Notre approche s'articule autour de la modélisation du besoin opérationnel et de l'exploration ciblée du Web. La modélisation du besoin informationnel permet de guider l'exploration du web pour découvrir et fournir des sources pertinentes à l'expert
The constant growth of the Web in recent years has made more difficult the discovery of new sources of information on a given topic. This is a prominent problem for Expert in Intelligence Analysis (EIA) who are faced with the search of pages on specific and sensitive topics. Because of their lack of popularity or because they are poorly indexed due to their sensitive content, these pages are hard to find with traditional search engine. In this article, we describe a new Web source discovery system called DOWSER. The goal of this system is to provide users with new sources of information related to their needs without considering the popularity of a page unlike classic Information Retrieval tools. The expected result is a balance between relevance and originality, in the sense that the wanted pages are not necessary popular. DOWSER in based on a user profile to focus its exploration of the Web in order to collect and index only related Web documents

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Jeunet, Camille. "Understanding & Improving Mental-Imagery Based Brain-Computer Interface (Mi-Bci) User-Training : towards A New Generation Of Reliable, Efficient & Accessible Brain- Computer Interfaces." Thesis, Bordeaux, 2016. http://www.theses.fr/2016BORD0221/document.

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Les Interfaces Cerveau-Ordinateur basées sur l’Imagerie Mentale (IM-ICO) permettent auxutilisateurs d’interagir uniquement via leur activité cérébrale, grâce à la réalisation de tâchesd’imagerie mentale. Cette thèse se veut contribuer à l’amélioration des IM-ICO dans le but deles rendre plus utilisables. Les IM-ICO sont extrêmement prometteuses dans de nombreuxdomaines allant de la rééducation post-AVC aux jeux-vidéo. Malheureusement, leurdéveloppement est freiné par le fait que 15 à 30% des utilisateurs seraient incapables de lescontrôler. Nombre de travaux se sont focalisés sur l’amélioration des algorithmes de traitementdu signal. Par contre, l’impact de l’entraînement des utilisateurs sur leur performance estsouvent négligé. Contrôler une IM-ICO nécessite l’acquisition de compétences et donc unentraînement approprié. Or, malgré le fait qu’il ait été suggéré que les protocolesd’entraînement actuels sont théoriquement inappropriés, peu d’efforts sont mis en oeuvre pourles améliorer. Notre principal objectif est de comprendre et améliorer l’apprentissage des IMICO.Ainsi, nous cherchons d’abord à acquérir une meilleure compréhension des processussous-tendant cet apprentissage avant de proposer une amélioration des protocolesd’entraînement afin qu’ils prennent en compte les facteurs cognitifs et psychologiquespertinents et qu’ils respectent les principes issus de l’ingénierie pédagogique. Nous avonsainsi défini 3 axes de recherche visant à investiguer l’impact (1) de facteurs cognitifs, (2) de lapersonnalité et (3) du feedback sur la performance. Pour chacun de ces axes, nous décrivonsd’abord les études nous ayant permis de déterminer les facteurs impactant la performance ;nous présentons ensuite le design et la validation de nouvelles approches d’entraînementavant de proposer des perspectives de travaux futurs. Enfin, nous proposons une solution quipermettrait d’étudier l’apprentissage de manière mutli-factorielle et dynamique : un systèmetutoriel intelligent
Mental-imagery based brain-computer interfaces (MI-BCIs) enable users to interact with theirenvironment using their brain-activity alone, by performing mental-imagery tasks. This thesisaims to contribute to the improvement of MI-BCIs in order to render them more usable. MIBCIsare bringing innovative prospects in many fields, ranging from stroke rehabilitation tovideo games. Unfortunately, most of the promising MI-BCI based applications are not yetavailable on the public market since an estimated 15 to 30% of users seem unable to controlthem. A lot of research has focused on the improvement of signal processing algorithms.However, the potential role of user training in MI-BCI performance seems to be mostlyneglected. Controlling an MI-BCI requires the acquisition of specific skills, and thus anappropriate training procedure. Yet, although current training protocols have been shown tobe theoretically inappropriate, very little research is done towards their improvement. Our mainobject is to understand and improve MI-BCI user-training. Thus, first we aim to acquire a betterunderstanding of the processes underlying MI-BCI user-training. Next, based on thisunderstanding, we aim at improving MI-BCI user-training so that it takes into account therelevant psychological and cognitive factors and complies with the principles of instructionaldesign. Therefore, we defined 3 research axes which consisted in investigating the impact of(1) cognitive factors, (2) personality and (3) feedback on MI-BCI performance. For each axis,we first describe the studies that enabled us to determine which factors impact MI-BCIperformance; second, we describe the design and validation of new training approaches; thethird part is dedicated to future work. Finally, we propose a solution that could enable theinvestigation of MI-BCI user-training using a multifactorial and dynamic approach: an IntelligentTutoring System

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Silva, Jesús, Naveda Alexa Senior, Suarez Ramiro Gamboa, Palma Hugo Hernández, and Núẽz William Niebles. "Method for Collecting Relevant Topics from Twitter supported by Big Data." Institute of Physics Publishing, 2020. http://hdl.handle.net/10757/652145.

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There is a fast increase of information and data generation in virtual environments due to microblogging sites such as Twitter, a social network that produces an average of 8, 000 tweets per second, and up to 550 million tweets per day. That's why this and many other social networks are overloaded with content, making it difficult for users to identify information topics because of the large number of tweets related to different issues. Due to the uncertainty that harms users who created the content, this study proposes a method for inferring the most representative topics that occurred in a time period of 1 day through the selection of user profiles who are experts in sports and politics. It is calculated considering the number of times this topic was mentioned by experts in their timelines. This experiment included a dataset extracted from Twitter, which contains 10, 750 tweets related to sports and 8, 758 tweets related to politics. All tweets were obtained from user timelines selected by the researchers, who were considered experts in their respective subjects due to the content of their tweets. The results show that the effective selection of users, together with the index of relevance implemented for the topics, can help to more easily find important topics in both sport and politics.

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Junior, Plinio Thomaz Aquino. "PICaP: padrões e personas para expressão da diversidade de usuários no projeto de interação." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/3/3141/tde-15092008-144412/.

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A acomodação da diversidade de perfil de usuários no projeto de interface de sistemas é um problema freqüente nas atividades do projetista da interação homem-computador. Conseqüentemente, o usuário encontra barreiras ao utilizar interfaces que não foram produzidas para o seu perfil. Este trabalho apresenta uma solução, destinada aos projetistas de famílias de sistemas interativos, para a acomodação e expressão da diversidade por meio da criação e uso de padrões de interface em camadas de personas - as PICAPs. Neste conceito, os padrões de interface apóiam o projetista no direcionamento de soluções, pois representam um problema recorrente e uma solução abstrata para o problema, de tal modo que esta solução pode ser aplicada em várias instâncias diferentes do mesmo problema. As personas apóiam a caracterização dos perfis dos usuários que são foco do projeto de interface, possibilitando que o projetista aplique soluções de interface de acordo com o usuário. O conceito foi aplicado no contexto de governo eletrônico, pois tais sistemas devem ser usáveis por todos, em distinção de qualquer natureza, sendo assim um exemplo da necessidade de se considerar a diversidade. Uma pesquisa com 25 projetistas foi feita para avaliação da aplicabilidade do conceito.
Accommodating users\' profile diversity in systems interface projects is a frequent problem for the human computer interface designer. Therefore, his/her user is faced with barriers in the use of interfaces which were not designed for his/her profile. This work presents a solution for expressing and accommodating users\' diversity, which is useful for the HCI designer, especially for those who design families of products. PICAPS are interface design patterns with layers indexed by personas. The interface design patterns support the designer in employing proven solutions, for they represent a recurrent problem and its abstract solution in such a way that this solution can be applied to different instantiations of the same problem. PICAPs are structured in multiple layers to make possible the users\' diversity accommodation. The layers are indexed by personas as user\'s characterization resource. This concept has been applied to electronic government services, because such systems should be usable by any citizen and therefore are a good example of the user diversity problem. A field research with 25 designers has been performed to check the concept´s applicability.

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Chouchani, Nadia. "Une approche de détection des communautés d'intérêt dans les réseaux sociaux : application à la génération d'IHM personnalisées." Thesis, Valenciennes, 2018. http://www.theses.fr/2018VALE0048/document.

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De nos jours, les Réseaux Sociaux sont omniprésents dans tous les aspects de la vie. Une fonctionnalité fondamentale de ces réseaux est la connexion entre les utilisateurs. Ces derniers sont engagés progressivement à contribuer en ajoutant leurs propres contenus. Donc, les Réseaux Sociaux intègrent également les créations des utilisateurs ; ce qui incite à revisiter les méthodes de leur analyse. Ce domaine a conduit désormais à de nombreux travaux de recherche ces dernières années. L’un des problèmes principaux est la détection des communautés. Les travaux de recherche présentés dans ce mémoire se positionnent dans les thématiques de l’analyse sémantique des Réseaux Sociaux et de la génération des applications interactives personnalisées. Cette thèse propose une approche pour la détection des communautés d’intérêt dans les Réseaux Sociaux. Cette approche modélise les données sociales sous forme d’un profil utilisateur social représenté par un ontologie. Elle met en oeuvre une méthode pour l’Analyse des Sentiments basées sur les phénomènes de l’influence sociale et d’Homophilie. Les communautés détectées sont exploitées dans la génération d’applications interactives personnalisées. Cette génération est basée sur une approche de type MDA, indépendante du domaine d’application. De surcroît, cet ouvrage fait état d’une évaluation de nos propositions sur des données issues de Réseaux Sociaux réels
Nowadays, Social Networks are ubiquitous in all aspects of life. A fundamental feature of these networks is the connection between users. These are gradually engaged to contribute by adding their own content. So Social Networks also integrate user creations ; which encourages researchers to revisit the methods of their analysis. This field has now led to a great deal of research in recent years. One of the main problems is the detection of communities. The research presented in this thesis is positioned in the themes of the semantic analysis of Social Networks and the generation of personalized interactive applications. This thesis proposes an approach for the detection of communities of interest in Social Networks. This approach models social data in the form of a social user profile represented by an ontology. It implements a method for the Sentiment Analysis based on the phenomena of social influence and homophily. The detected communities are exploited in the generation of personalized interactive applications. This generation is based on an approach of type MDA, independent of the application domain. In addition, this manuscript reports an evaluation of our proposals on data from Real Social Networks

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Scheid, Fernando. "Acesso e utilização a bases de dados: estudo de caso da Biblioteca do IFSul – Câmpus Charqueadas." Universidade do Vale do Rio dos Sinos, 2017. http://www.repositorio.jesuita.org.br/handle/UNISINOS/6666.

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Submitted by JOSIANE SANTOS DE OLIVEIRA (josianeso) on 2017-10-03T12:30:12Z No. of bitstreams: 1 Fernando Scheid_.pdf: 1316185 bytes, checksum: 82e933449d1319408b251dc78485aee2 (MD5)
Made available in DSpace on 2017-10-03T12:30:13Z (GMT). No. of bitstreams: 1 Fernando Scheid_.pdf: 1316185 bytes, checksum: 82e933449d1319408b251dc78485aee2 (MD5) Previous issue date: 2017-07-18
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Este trabalho tem por objetivo realizar umestudo sobre o conhecimento e a utilização de bases de dados em pesquisas por parte dos alunos da graduação e pós-graduação do Instituto Federal Sul-rio-grandense Câmpus Charqueadas, tendo como cenário principal a Biblioteca com a finalidade de compreender o perfil de pesquisa desses usuários. A metodologia utilizada foi um estudo de caso e como instrumentos de coleta de dados, dois questionários: o primeiro questionário com questões fechadas incluindo comentários e sugestões e outro questionário, posteriormente, com perguntas abertas. Após a análise da coleta de dados chegou-se à conclusão de que muitos usuários desconhecem ou não utilizam bases de dados (51%) para realizarem suas pesquisas, porém as bases de dados mais conhecidas são Scielo, Portal de Periódicos da Capes e Web of Science. O curso de pós-graduação utiliza mais esses recursos em relação aos cursos de graduação, apesar de 19% afirmarem que desconhecem ou não utilizam bases de dados. Entre os sites de busca na internet o Google teve o maior destaque, com 65%. Como sugestão dos usuários está a realização de capacitações e treinamentos para que essas fontes de informação possam ser utilizadas com maior frequência. Por fim, esta pesquisa apresenta dois produtos: o diagnóstico com relação ao conhecimento e utilização de bases de dados em pesquisa pelos alunos do IFSul Câmpus Charqueadas e a proposta de um projeto de tutorial relativo à utilização de bases de dados em pesquisas para ser disponibilizado na página da Biblioteca, a fim de qualificar a busca por informações a partir de fontes online, oferecendo outra possibilidade de acesso a acervos.
This work aims to carry out a study about the knowledge and usage of data bases in researches done by the Graduation and Post-Graduation students of the Federal Institute Sul-rio-grandense, Campus Charqueadas, having the Library as the main scenario to understand the research profile of those users. The methodology used was a case study and the instruments of data collection were two questionnaires: the first questionnaire with closed questions including comments and suggestions and another questionnaire, used later, with open questions. After analyzing the data collection, it was concluded that many users are unaware or do not use databases (51%) to carry out their researches, but the most well-known databases are Scielo, Periódicos Capes and Web of Science. The postgraduate course uses these resources more in relation to undergraduate courses, although 19% state that they do not know or do not use databases. Among the search engines on the internet, Google had the biggest highlight, with 65%. As a suggestion of the users, the execution of training courses about these sources of information can be used more frequently. Finally, this research presents two products: the diagnosis regarding the knowledge and use of databases in research by the students of IFSul Campus Charqueadas and the proposal of a project of tutorial on the use of databases in researches to be available in Library website in order to qualify the search for information from online sources, offering another possibility of access to collections.

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Diallo, Mouhamadou Saliou. "Découverte de règles de préférences contextuelles : application à la construction de profils utilisateurs." Thesis, Tours, 2015. http://www.theses.fr/2015TOUR4052/document.

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L’utilisation de préférences suscite un intérêt croissant pour personnaliser des réponses aux requêtes et effectuer des recommandations ciblées. Pourtant, la construction manuelle de profils de préférences reste à la fois complexe et consommatrice de temps. Dans ce contexte, nous présentons dans cette thèse une nouvelle méthode automatique d’extraction de préférences basée sur des techniques de fouille de données. L’approche que nous proposons est constituée de deux phases : (1) une phase d’extraction de toutes les règles de préférences contextuelles intéressantes et (2) une phase de construction du profil utilisateur. A la fin de la première phase, nous constatons qu’il y a des règles redondantes voir superflues ; la seconde phase permet d’éliminer les règles superflues afin d’avoir un profil concis et consistant. Dans notre approche, un profil utilisateur est constitué de cet ensemble de règles de préférences contextuelles résultats de la seconde phase. La consistance garantit que les règles de préférences spécifiant les profils sont en accord avec un grand nombre de préférences utilisateur et contredisent un petit nombre d’entre elles. D’autre part, la concision implique que les profils sont constitués d’un petit nombre de règles de préférences. Nous avons aussi proposé quatre méthodes de prédiction qui utilisent les profils construits. Nous avons validé notre approche sur une base de données de films construite à partir de MovieLens et IMDB. La base de données contient 3 881 films notés par 6 040 utilisateurs. Ces derniers ont attribué 800 156 notes. Les résultats de ces expériences démontrent que la concision des profils utilisateurs est contrôlée par le seuil d’accord minimal et que même avec une forte réduction du nombre de règles, les qualités de prédiction des profils restent à un niveau acceptable. En plus des expérimentations montrant la qualité de prédiction de notre approche, nous avons montré également que les performances de notre approche peuvent rivaliser avec les qualités de prédiction de certaines méthodes de l’état de l’art, en particulier SVMRank
The use of preferences arouses a growing interest to personalize response to requests and making targeted recommandations. Nevertheless, manual construction of preferences profiles remains complex and time-consuming. In this context, we present in this thesis a new automatic method for preferences elicitation based on data mining techniques. Our proposal is a two phase algorithm : (1) Extracting all contextual preferences rules from a set of user preferences and (2) Building user profile. At the end of the first phase, we notice that there is to much preference rules which satisfy the fixed constraints then in the second phase we eliminate the superfluous preferences rules. In our approach a user profile is constituted by the set of contextual preferences rules resulting of the second phase. A user profile must satisfy conciseness and soundness properties. The soundness property guarantees that the preference rules specifying the profiles are in agreement with a large set of the user preferences, and contradict a small number of them. On the other hand, conciseness implies that profiles are small sets of preference rules. We also proposed four predictions methods which use the extracted profiles. We validated our approach on a set of real-world movie rating datasets built from MovieLens and IMDB. The whole movie rating database consists of 800,156 votes from 6,040 users about 3,881 movies. The results of these experiments demonstrates that the conciseness of user profiles is controlled by the minimal agreement threshold and that even with strong reduction, the soundness of the profile remains at an acceptable level. These experiment also show that predictive qualities of some of our ranking strategies outperform SVMRank in several situations

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Aissaoui, Djamel. "Diagnostic des déficits et des besoins liés au vieillissement : apports pour la conception de gérontotechnologies." Thesis, Paris 8, 2018. http://www.theses.fr/2018PA080031/document.

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Le vieillissement observé dans la population est souvent responsable de déficits amenant une perte d’autonomie, et une situation de handicap plus ou moins importante. Ces difficultés n’ont pas toujours de possibilités thérapeutiques (i.e. médicamenteuses ou chirurgicales). En revanche, il faut pouvoir soigner, diminuer ou neutraliser ces symptômes. Les technologies numériques semblent pouvoir jouer un rôle sur certaines manifestations du vieillissement en aidant, en assistant, en stimulant, en rééduquant, et, in fine, fournir davantage de qualité de vie et d’autonomie.Cependant, cette nouvelle opportunité a du mal à trouver sa place auprès des seniors, pour des raisons aussi diverses que complexes. En effet, la mise en place, l’organisation, l’évaluation, l’acceptation, le diagnostic, etc. sont autant d’obstacles à l’intégration des technologies. Toutefois, on remarque que le frein le plus important semble être la conception de ces technologies elles-mêmes. Effectivement, pour concevoir, les professionnels doivent avoir de multiples compétences et savoir analyser les besoins, poser des diagnostics compliqués avec des tableaux cliniques et environnementaux multiples (i.e. polypathologie, polyhandicap, évaluation de l’environnement, etc.), pour fournir l’ensemble des solutions ergonomiques, techniques et technologiques possibles. Pour autant, les profils orientés conception (i.e. informaticiens, ingénieurs, architectes, etc.) auxquels appartiennent, au final, la conception et la fabrication des technologies, ont peu de compétences d’évaluation globale et multidimensionnelle d’un sujet en perte d’autonomie et de son environnement.Cette thèse a pour objectif d’apporter un outil informatique capable d’être une aide concrète pour les professionnels de la santé, de la réinsertion et de la conception, en leur proposant une méthodologie d’analyse des déficits sous forme d’un profil précis des potentiels, des freins, et de l’environnement. Pour cela, notre travail tient compte de la pluridisciplinarité des professionnels, et de la complexité de l’évaluation gériatrique.Notre démarche est basée sur un outil informatique ayant plusieurs avantages : d’une part, donner une check-list afin d’être au maximum exhaustif dans l’évaluation des déficits liés à l’âge et ainsi éviter les erreurs ou les oublis lors de l’évaluation. D’autre part, permettre une standardisation par l’administration de tests précis, et ainsi donner un profil à la fois quantitatif et qualitatif de la personne et de son environnement. Enfin, notre méthodologie fournit également une évaluation des systèmes technologiques destinés aux seniors. Notre système, baptisé DAD « Design for Adapted Device » est conçu selon un modèle de conception centré utilisateurs. Nous avons consulté en préconception nos utilisateurs primaires (i.e. sujets âgés), et nous avons relevé dans notre état de l’art les tests d’évaluation de références. Ensuite, nous avons mis au point plusieurs prototypes que nous avons testés auprès de nos utilisateurs secondaires (i.e. professionnels du diagnostic). Enfin, nous avons conçu notre logiciel dans sa version finale, et nous avons soumis des professionnels de la gérontologie (i.e. des professionnels médico-sociaux et des profils orienté conception) à des tests face à des patients. Les résultats issus de nos tests sont très encourageants et suggèrent que notre outil est fidèle et valide.L’outil devrait sensibiliser, inciter et guider les différents producteurs de technologies (i.e. industriel, designer, informaticien ingénieur, etc.), ainsi que les acteurs de santé (i.e. médecin, infirmier, kinésithérapeute, ergothérapeute, psychologue, etc.) à intégrer les personnes âgées dans leur prise en charge, dans leurs décisions, ou dans les différents projets qu’ils envisagent de mettre en place (e.g. conception, prescription, suivi, etc.)
The observed aging of the population is often responsible of deficits causing a loss of autonomy & handicap situation which turns to be more and more important. The encountered difficulties do not always have therapeutic alternatives (i.e. neither through drugs nor surgery). However, having the symptoms treated, reduced or neutralized is a must. The digital technologies seem capable to play a role on aging consequences, on quality of life & autonomy helping, assisting, stimulating, reeducating elderly population.Nevertheless, the digital opportunity does not seem to have success among elderly people for many different & complex reasons. Fair to underline that challenges are faced while trying to integrate these technologies : set up, organization, assessment, acceptance, diagnosis etc. The biggest challenge though remains the design of the technology itself. In fact, professionals need to have multiple competences and know how to analyze requirements, diagnose through multiple clinical & environment situations (multiple pathologies, multiple disabilities, environment assessment, etc.) in order to propose exhaustive ergonomic, technical & technological solutions. Having this said, the profiles who are design oriented (e.g. IT, engineers, architects, etc.) and who own the design & build of the technologies have limited capacities in global, multidimensional assessment on autonomy loss & its environment.Our thesis aims at proposing a digital device able to help concretely professionals specialized in healthcare, reintegration, and design while providing a methodology to analyze deficits through precise profiling of environment, potentials and constraints. That is the reason why, our work considers professionals’ multidisciplinary, geriatrics complex assessment.Our approach consists on an IT device with has multiple advantages: a check list in order to evaluate deficiencies linked to aging and prevent mistakes or omissions during the assessment ;a standardization through precise testing ;a definition of a qualitative & quantitative profile of the person and the environment ;a strong assessment of the digital technologies focusing on elderly population.Our tool, named DAD « Design for Adapted Device » was designed according to a model focusing on users. At the very first step of the design, primary users (i.e. elderly patients) were consulted and in the conceptual framework, we picked the gold standards. Then, we launched several prototypes which were subjects to testing by our secondary users (i.e. diagnosis professionals). Last but not least, we designed the final version of our tool and we had gerontology professionals (medico-social professionals & design oriented profiles) going through tests in front of patients. Our testing results looked encouraging and suggest that our tool is reliable and valid.The tool should sensitive, encourage and guide the digital actors (such as industrials, designers, IT engineers, etc.) as well as health professionals (such as doctors, nurses, physiotherapists, ergotherapists, psychologists, etc.) to strongly consider elderly patients in their therapeutic approaches, in their decision making or in their different to-be projects (e.g. design, prescription and follow up, etc.)

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50

Mou, Lei. "Toward a customized privacy preservation method in mobile tourism applications." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAM063.

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Abstract:

Le développement rapide des TIC (Information and Communication Technology) a un impact énorme à toutes les industries. Internet Mobile, Web 2.0, la technologie de positionnement sont déployées dans le monde largement, qui a initialisé la demande intérieure des nouvelles technologies dans le domaine du tourisme. En profitant de la commodité apportée par les nouvelles technologies, de plus en plus d'utilisateurs de commencer à se concentrer sur les questions de confidentialité.Comme on le sait, il y a une contradiction entre la qualité des services et la vie privée recommandés basés sur la localisation. profil de l'utilisateur détaillé et informations de localisation précises sont nécessaires pour fournir un service basé sur la localisation avec une grande efficacité et de qualité, tandis que la préservation de la vie privée exige cacher le profil et l'emplacement de l'utilisateur. De nombreuses recherches récentes vise à trouver un équilibre entre eux, pour obtenir la meilleure qualité de la LBS dans le contexte du contenu du profil de l'utilisateur et les informations de localisation moins exposée.Dans cette thèse, l'auteur a porté principalement sur la vie privée de profil de l'utilisateur mobile, qui couvre à la fois les caractéristiques personnelles et les informations de localisation.1, sur mesure modèle de confidentialité des utilisateurs considérant à la fois les qualités personnelles et la localisation spatiale et temporelle est définie pour l'utilisateur mobile.Dans cette recherche, nous avons proposé le modèle de confidentialité personnalisé pour chaque utilisateur de définir, son / sa propre signification de la vie privée. Avec ce modèle, à des fins de Voyage différents, ou même pour le temps et un autre emplacement, ils peuvent avoir des définitions différentes pour leur vie privée.2, Minimiser les données à stocker sur le serveur.Les profils sont stockés de deux façons différentes, le profil complet est stocké sur le côté client, et seules les valeurs des attributs qui sont en mesure pour les utilisateurs de partager sont stockés sur le côté serveur, ainsi minimisé les données à stocker sur le serveur.3, les niveaux personnalisés de granularité de la divulgation de l'emplacement et l'heure sont réglables pour les utilisateurs.Pour changer fréquemment des attributs tels que l'emplacement et l'heure, l'utilisateur peut les divulguer avec une granularité appropriée, afin d'obtenir le service attendu par les fournisseurs de services.Mots-clés: vie privée, l'emplacement, le profil de l'utilisateur, mobile, tourisme
The rapid development of ICT(Information and Communication Technology) brought huge impact to all industries. Mobile internet, Web 2.0, positioning technology are deployed world-widely, that initialized inner request of new technologies in the field of tourism as well. By enjoying the convenience brought by new technologies, more and more users starting to focus on privacy issues.As known, there is a contradiction between the quality of recommended location-based services and privacy. Detailed user profile and precise location information are needed for providing location-based service with high efficiency and quality, while privacy preservation requires hiding user's profile and location. Many recent researches aims to seek a balance between them, to obtain the best quality of the LBS in the context of the least exposed user profile content and location information.In this thesis, the author focused mainly on the privacy of mobile user profile, which covers both personal characteristics and location information.1, Customized user privacy model considering both personal attributes and spatial and temporal location is defined for mobile user.In this research, we proposed customized privacy model for every user to define, his/her own meaning of privacy. With this model, for different travel purpose, or even for different time and location, they can have different definitions for their privacy.2, Minimized the data to be stored on server.Profiles are stored in two different ways, complete profile is stored on the client side, and only the values of the attributes that are able for the users to share are stored on the server side, thus minimized the data to be stored on server.3, Customized levels of granularity of disclosure of location and time are adjustable for users.For frequently changing attributes such as location and time, user can disclose them with suitable granularity, in order to obtain expected service from the service providers.Keywords: privacy, location, user profile, mobile, tourism

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