Academic literature on the topic 'Ubiquitous User Query Model'

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Journal articles on the topic "Ubiquitous User Query Model"

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Akram, Atia, Asma Ahmad Farhan, and Amna Basharat. "Less is more: Efficient behavioral context recognition using Dissimilarity-Based Query Strategy." PLOS ONE 18, no. 6 (June 7, 2023): e0286919. http://dx.doi.org/10.1371/journal.pone.0286919.

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With the advancement of ubiquitous computing, smartphone sensors are generating a vast amount of unlabeled data streams ubiquitously. This sensor data can potentially help to recognize various behavioral contexts in the natural environment. Accurate behavioral context recognition has a wide variety of applications in many domains like disease prevention and independent living. However, despite the availability of enormous amounts of sensor data, label acquisition, due to its dependence on users, is still a challenging task. In this work, we propose a novel context recognition approach i.e., Dissimilarity-Based Query Strategy (DBQS). Our approach DBQS leverages Active Learning based selective sampling to find the informative and diverse samples in the sensor data to train the model. Our approach overcomes the stagnation problem by considering only new and distinct samples from the pool that were not previously explored. Further, our model exploits temporal information in the data in order to further maintain diversity in the dataset. The key intuition behind the proposed approach is that the variations during the learning phase will train the model in diverse settings and it will outperform when assigned a context recognition task in the natural setting. Experimentation on a publicly available natural environment dataset demonstrates that our proposed approach improved overall average Balanced Accuracy(BA) by 6% with an overall 13% less training data requirement.
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Kritsi, Eftichia, Minos-Timotheos Matsoukas, Constantinos Potamitis, Anastasia Detsi, Marija Ivanov, Marina Sokovic, and Panagiotis Zoumpoulakis. "Novel Hit Compounds as Putative Antifungals: The Case of Aspergillus fumigatus." Molecules 24, no. 21 (October 25, 2019): 3853. http://dx.doi.org/10.3390/molecules24213853.

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The prevalence of invasive fungal infections has been dramatically increased as the size of the immunocompromised population worldwide has grown. Aspergillus fumigatus is characterized as one of the most widespread and ubiquitous fungal pathogens. Among antifungal drugs, azoles have been the most widely used category for the treatment of fungal infections. However, increasingly, azole-resistant strains constitute a major problem to be faced. Towards this direction, our study focused on the identification of compounds bearing novel structural motifs which may evolve as a new class of antifungals. To fulfil this scope, a combination of in silico techniques and in vitro assays were implemented. Specifically, a ligand-based pharmacophore model was created and served as a 3D search query to screen the ZINC chemical database. Additionally, molecular docking and molecular dynamics simulations were used to improve the reliability and accuracy of virtual screening results. In total, eight compounds, bearing completely different chemical scaffolds from the commercially available azoles, were proposed and their antifungal activity was evaluated using in vitro assays. Results indicated that all tested compounds exhibit antifungal activity, especially compounds 1, 2, and 4, which presented the most promising minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) values and, therefore, could be subjected to further hit to lead optimization.
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Et. al., Niraja Jain,. "Data Membership Identification using Bloom Filter in Cloud Storage for Effective Resource Allocation." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 2 (March 21, 2021): 102–8. http://dx.doi.org/10.17762/itii.v9i2.308.

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Cloud computing has recently been the buzz word that had changed the entire software industry with its PaaS, IaaS and SaaS architecture model. The legacy systems operational in the organizations across different industries have been using the database that had an overhead in terms of cost of data storage, runtime operation and frequent data maintenance. Cloud database concept had challenged the existing storage and operational norms of data. In the distributed environment, resources used in the cloud databases need to identify whether the requested data belongs to the data nodes of a cluster. With databases began to be ubiquitous, the data storage needed to satisfy heterogeneous data structures rather the unstructured data storage support is looked for. The Use of Bloom's filter for data membership identification is the novel approach and can effectively improve the resource organization strategy on cloud. Dynamic resource organization can further improve the query efficiency as well. The concern raised during this is the data privacy which can also be ascertain by maintaining the data access authority levels. Bloom filter uses less memory space against the large dataset to store it's information. A Bloom filter is proposed to be used to determine whether an element is part of a reference set. It is a very compact hash-based data structure with efficient look-up times and a manageable risk of giving false positives.
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Zhang, Bo, Xiaoxuan Qi, and Xiaowei Han. "An Advanced User Intent Model Based On User Learning Process." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 09 (December 13, 2019): 2050024. http://dx.doi.org/10.1142/s021800142050024x.

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User intent analysis is a continuous research hotspot in the field of query expansion. However, the big amount of irrelevant feedbacks in search log has negatively impacted the precision of user intent model. By observing the log, it can be found that tentative click is a major source of irrelevant feedback. It is also observed that a kind of new feedback information can be extracted from the log to recognize the characteristics of tentative clicks. With this new feedback information, this paper proposes an advanced user intent model and applies it into query expansion. Experiment results show that the model can effectively decrease the negative impact of irrelevant feedbacks that belong to tentative clicks and increase the precision of query expansion, especially for those informational queries.
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Yu, Yang Xin. "Personalization Information Retrieval Based on Unigram Language Model." Applied Mechanics and Materials 321-324 (June 2013): 2269–73. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.2269.

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Personalization information retrieval is very useful in information retrieval system, the user profile can be used to represent the favorites or interests of user. Many methods to personalization have been studied in extending query with user profile. A proposed navel method which use the context of long-term user profile with multiple domain to extend query model under the unigram language model framework, uses the new query model to retrieve and get more interesting results for users. Combined with psudo relevance feedback model, the proposed method get better performance. Experimental results show that the proposed method in this paper is effective.
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Bhalerao, R. S., Dhananjay Kumbhakarna, Ashvini Avhad, Kirti Shinde, and Dipalee Tidke. "Design Enrichment of Query Forms for Database Query." Asian Journal of Computer Science and Technology 5, no. 1 (May 5, 2016): 30–35. http://dx.doi.org/10.51983/ajcst-2016.5.1.1761.

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The scientific databases & web databases maintain huge and large amount of data. The real-world databases contain over thousands of relations & attributes. predefined database query forms are not able to satisfy various queries from users on those databases. The review of DQF is to capture a user’s preference and rating query form components, assisting to take decisions. The creation of a query form is an faster process and is given by the user. A user can also create the query form and submit queries to view the query output at each iteration. This way, a query form could be dynamically created till the user satisfies with the query forms. The important F-measure for measuring the goodness of a query form. A model is developed for estimating the goodness of a query form in DQF. Experimental evaluation and user study demonstrate the accuracy and performance of the system. The ranking of form components is based on the captured user preference. A user can also fill the query form and submit queries to view the query output at each step. This type a query form could be dynamically refined till the user satisfies with the query results.
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Chen, Wanyu, Zepeng Hao, Taihua Shao, and Honghui Chen. "Personalized query suggestion based on user behavior." International Journal of Modern Physics C 29, no. 04 (April 2018): 1850036. http://dx.doi.org/10.1142/s0129183118500365.

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Query suggestions help users refine their queries after they input an initial query. Previous work mainly concentrated on similarity-based and context-based query suggestion approaches. However, models that focus on adapting to a specific user (personalization) can help to improve the probability of the user being satisfied. In this paper, we propose a personalized query suggestion model based on users’ search behavior (UB model), where we inject relevance between queries and users’ search behavior into a basic probabilistic model. For the relevance between queries, we consider their semantical similarity and co-occurrence which indicates the behavior information from other users in web search. Regarding the current user’s preference to a query, we combine the user’s short-term and long-term search behavior in a linear fashion and deal with the data sparse problem with Bayesian probabilistic matrix factorization (BPMF). In particular, we also investigate the impact of different personalization strategies (the combination of the user’s short-term and long-term search behavior) on the performance of query suggestion reranking. We quantify the improvement of our proposed UB model against a state-of-the-art baseline using the public AOL query logs and show that it beats the baseline in terms of metrics used in query suggestion reranking. The experimental results show that: (i) for personalized ranking, users’ behavioral information helps to improve query suggestion effectiveness; and (ii) given a query, merging information inferred from the short-term and long-term search behavior of a particular user can result in a better performance than both plain approaches.
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Zhou, Yinglian, and Jifeng Chen. "Time Series Geographic Social Network Dynamic Preference Group Query." International Journal of Information Systems in the Service Sector 13, no. 4 (October 2021): 18–39. http://dx.doi.org/10.4018/ijisss.2021100102.

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Driven by experience and social impact of the new life, user preferences continue to change over time. In order to make up for the shortcomings of existing geographic social network models that often cannot obtain user dynamic preferences, a time-series geographic social network model was constructed to detect user dynamic preferences, a dynamic preference value model was built for user dynamic preference evaluation, and a dynamic preferences group query (DPG) was proposed in this paper . In order to optimize the efficiency of the DPG query algorithm, the UTC-tree index user timing check-in record is designed. UTC-tree avoids traversing all user check-in records in the query, accelerating user dynamic preference evaluation. Finally, the DPG query algorithm is used to implement a well-interacted DPG query system. Through a large number of comparative experiments, the validity of UTC-tree and the scalability of DPG query are verified.
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Riezler, Stefan, and Yi Liu. "Query Rewriting Using Monolingual Statistical Machine Translation." Computational Linguistics 36, no. 3 (September 2010): 569–82. http://dx.doi.org/10.1162/coli_a_00010.

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Long queries often suffer from low recall in Web search due to conjunctive term matching. The chances of matching words in relevant documents can be increased by rewriting query terms into new terms with similar statistical properties. We present a comparison of approaches that deploy user query logs to learn rewrites of query terms into terms from the document space. We show that the best results are achieved by adopting the perspective of bridging the “lexical chasm” between queries and documents by translating from a source language of user queries into a target language of Web documents. We train a state-of-the-art statistical machine translation model on query-snippet pairs from user query logs, and extract expansion terms from the query rewrites produced by the monolingual translation system. We show in an extrinsic evaluation in a real-world Web search task that the combination of a query-to-snippet translation model with a query language model achieves improved contextual query expansion compared to a state-of-the-art query expansion model that is trained on the same query log data.
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Gou, Zhinan, and Yan Li. "A method of query expansion based on topic models and user profile for search in folksonomy." Journal of Intelligent & Fuzzy Systems 41, no. 1 (August 11, 2021): 1701–11. http://dx.doi.org/10.3233/jifs-210508.

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With the development of the web 2.0 communities, information retrieval has been widely applied based on the collaborative tagging system. However, a user issues a query that is often a brief query with only one or two keywords, which leads to a series of problems like inaccurate query words, information overload and information disorientation. The query expansion addresses this issue by reformulating each search query with additional words. By analyzing the limitation of existing query expansion methods in folksonomy, this paper proposes a novel query expansion method, based on user profile and topic model, for search in folksonomy. In detail, topic model is constructed by variational antoencoder with Word2Vec firstly. Then, query expansion is conducted by user profile and topic model. Finally, the proposed method is evaluated by a real dataset. Evaluation results show that the proposed method outperforms the baseline methods.
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Dissertations / Theses on the topic "Ubiquitous User Query Model"

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Moran, Stuart. "User perceptions of system attributes in ubiquitous monitoring : toward a model of behavioural intention." Thesis, University of Reading, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.541983.

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Gil, Pascual Miriam. "Adapting Interaction Obtrusiveness: Making Ubiquitous Interactions Less Obnoxious. A Model Driven Engineering approach." Doctoral thesis, Universitat Politècnica de València, 2013. http://hdl.handle.net/10251/31660.

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La Computaci'on Ubicua plantea proveer de inteligencia a nuestros entornos ofreciendo servicios a los usuarios que permitan ayudarlos en su vida cotidiana. Con la inclusi'on de dispositivos ubicuos en nuestra vida (por ejemplo los dispositivos m'oviles), los usuarios hemos pasado a estar siempre conectados al entorno, pudiendo interactuar con el. Sin embargo, a diferencia de las interacciones de escritorio tradicionales donde los usuarios eran quienes ped'¿an informaci'on o introduc'¿an datos, las interacciones ubicuas tienen que lidiar con un entorno de los usuarios variable, demandando uno de los recursos mas valiosos para los usuarios: la atenci'on humana. De esta forma, un reto en el paradigma de computaci'on ubicua es regular las peticiones de atenci'on del usuario. Esto implica que las interacciones de los servicios deber'¿an comportarse de una manera ¿considerada¿ teniendo en cuenta el grado en que cada servicio se inmiscuye en la mente del usuario (el nivel de molestia). Partiendo de las bases de la Ingenier'¿a Dirigida por Modelos (MDE) y de los principios de la Computaci'on Considerada, esta tesis se orienta a dise¿nar y desarrollar servicios que sean capaces de adaptar sus interacciones de acuerdo a la atenci'on del usuario en cada momento. El principal objetivo de esta tesis es introducir capacidades de adaptaci'on considerada en los servicios ubicuos para proporcionar interacciones que no perturben al usuario. Esto lo conseguimos mediante un proceso de desarrollo que cubre desde el dise¿no de los servicios hasta su implementaci'on, centr'andose en los requisitos de adaptaci'on de la interacci'on particulares para cada usuario. Para el dise¿no del comportamiento de la interacci'on en base al nivel de molestia se han de¿nido unos modelos de intromisi'on e interacci'on independientes de la tecnolog'¿a. Estos modelos son los que posteriormente conducen la adaptaci'on de la interacci'on din'amicamente, por medio de una infraestructura aut'onoma que los usa en tiempo de ejecuci'on. Esta infraestructura es capaz de detectar cambios en la situaci'on del usuario (por ejemplo cambios en su localizaci'on, su actividad, etc.) y planear y ejecutar modi¿caciones en la interacci'on de los servicios. Cuando se detecta un cambio del contexto del usuario, los servicios se auto-adaptan para usar los componentes de interacci'on m'as apropiados de acuerdo a la nueva situaci'on y no molestar al usuario. Adem'as, como las necesidades y preferencias de los usuarios pueden cambiar con el tiempo, nuestra aproximaci'on utiliza la estrategia del aprendizaje por refuerzo para ajustar los modelos de dise¿no iniciales de forma que maximicemos la experiencia del usuario. El dise¿no inicial de la interacci'on basado en el nivel de molestia nos asegura un comportamiento inicial consistente con las necesidades de los usuarios en ese momento. Luego, este dise¿no se va re¿nando de acuerdo al comportamiento y preferencias de cada usuario por medio de su retroalimentaci'on a trav'es de la experiencia de uso. Adem'as, tambi'en proporcionamos una interfaz m'ovil que permite a los usuarios ¿nales personalizarse de forma manual los modelos en base a sus propias preferencias. El trabajo presentado en esta tesis se ha llevado a la pr'actica para su evaluaci'on desde el punto de vista de los dise¿nadores y de los usuarios ¿nales. Por una parte, el m'etodo de dise¿no se ha validado para comprobar que ayuda a los dise¿nadores a especi¿car este tipo de servicios. Pese a que el proceso de desarrollo no ofrece una automatizaci'on completa, las gu'¿as ofrecidas y la formalizaci'on de los conceptos implicados ha demostrado ser 'util a la hora de desarrollar servicios cuya interacci'on es no molesta. Por otra parte, la adaptaci'on de la interacci'on en base al nivel de molestia se ha puesto en pr'actica con usuarios para evaluar su satisfacci'on con el sistema y su experiencia de usuario. Esta validaci'on ha desvelado la importancia de considerar los aspectos de molestia en el proceso de adaptaci'on de la interacci'on para ayudar a mejorar la experiencia de usuario.
In Ubiquitous Computing environments, people are surrounded by a lot of embedded services. Since ubiquitous devices, such as mobile phones, have become a key part of our everyday life, they enable users to be always connected to the environment and interact with it. However, unlike traditional desktop interactions where users are used to request for information or input data, ubiquitous interactions have to face with variable user¿s environment, making demands on one of the most valuable resources of users: human attention. A challenge in the Ubiquitous Computing paradigm is regulating the request for user¿s attention. That is, service interactions should behave in a considerate manner by taking into account the degree in which each service intrudes the user¿s mind (i.e., the obtrusiveness degree). In order to prevent service behavior from becoming overwhelming, this work, based on Model Driven Engineering foundations and the Considerate Computing principles, is devoted to design and develop services that adapt their interactions according to user¿s attention. The main goal of the present thesis is to introduce considerate adaptation capabilities in ubiquitous services to provide non-disturbing interactions. We achieve this by means of a systematic method that covers from the services¿ design to their implementation and later adaptation of interaction at runtime
Gil Pascual, M. (2013). Adapting Interaction Obtrusiveness: Making Ubiquitous Interactions Less Obnoxious. A Model Driven Engineering approach [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/31660
TESIS
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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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Peker, Serhat. "A Novel User Activity Prediction Model For Context Aware Computing Systems." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613662/index.pdf.

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In the last decade, with the extensive use of mobile electronic and wireless communication devices, there is a growing need for context aware applications and many pervasive computing applications have become integral parts of our daily lives. Context aware recommender systems are one of the popular ones in this area. Such systems surround the users and integrate with the environment
hence, they are aware of the users'
context and use that information to deliver personalized recommendations about everyday tasks. In this manner, predicting user&rsquo
s next activity preferences with high accuracy improves the personalized service quality of context aware recommender systems and naturally provides user satisfaction. Predicting activities of people is useful and the studies on this issue in ubiquitous environment are considerably insufficient. Thus, this thesis proposes an activity prediction model to forecast a user&rsquo
s next activity preference using past preferences of the user in certain contexts and current contexts of user in ubiquitous environment. The proposed model presents a new approach for activity prediction by taking advantage of ontology. A prototype application is implemented to demonstrate the applicability of this proposed model and the obtained outputs of a sample case on this application revealed that the proposed model can reasonably predict the next activities of the users.
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Lewandowski, J. "Mobile application of artificial intelligence to vital signs monitoring : multi parametric, user adaptable model for ubiquitous well-being monitoring." Thesis, Coventry University, 2014. http://curve.coventry.ac.uk/open/items/fc80e93c-1a7e-419d-84c7-eaed12d4a953/1.

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Over the next decade, current reactive medicine, is expected to be replaced by a medicine increasingly focused on wellness so called personalised, predictive, preventive, and participatory (P4) will be less expensive, yet more accurate and effective.
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Tian, Hao. "A methodology for domain-specific conceptual data modeling and querying." restricted, 2007. http://etd.gsu.edu/theses/available/etd-02272007-140033/.

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Thesis (Ph. D.)--Georgia State University, 2007.
Rajshekhar Sunderraman, committee chair; Paul S. Katz, Yanqing Zhang, Ying Zhu, committee members. Electronic text (128 p. : ill.) : digital, PDF file. Description based on contents viewed Oct. 15, 2007; title from file title page. Includes bibliographical references (p. 124-128).
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Scarlato, Michele. "Sicurezza di rete, analisi del traffico e monitoraggio." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amslaurea.unibo.it/3223/.

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Il lavoro è stato suddiviso in tre macro-aree. Una prima riguardante un'analisi teorica di come funzionano le intrusioni, di quali software vengono utilizzati per compierle, e di come proteggersi (usando i dispositivi che in termine generico si possono riconoscere come i firewall). Una seconda macro-area che analizza un'intrusione avvenuta dall'esterno verso dei server sensibili di una rete LAN. Questa analisi viene condotta sui file catturati dalle due interfacce di rete configurate in modalità promiscua su una sonda presente nella LAN. Le interfacce sono due per potersi interfacciare a due segmenti di LAN aventi due maschere di sotto-rete differenti. L'attacco viene analizzato mediante vari software. Si può infatti definire una terza parte del lavoro, la parte dove vengono analizzati i file catturati dalle due interfacce con i software che prima si occupano di analizzare i dati di contenuto completo, come Wireshark, poi dei software che si occupano di analizzare i dati di sessione che sono stati trattati con Argus, e infine i dati di tipo statistico che sono stati trattati con Ntop. Il penultimo capitolo, quello prima delle conclusioni, invece tratta l'installazione di Nagios, e la sua configurazione per il monitoraggio attraverso plugin dello spazio di disco rimanente su una macchina agent remota, e sui servizi MySql e DNS. Ovviamente Nagios può essere configurato per monitorare ogni tipo di servizio offerto sulla rete.
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Gochhayat, Sarada Prasad. "Designing Solutions to Some of the Issues in Ubiquitous Networks." Thesis, 2016. https://etd.iisc.ac.in/handle/2005/4354.

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The inception of ubiquitous computing goes back to late eighties, when the Research at the Xerox Palo Alto Research (PARC) started designing ubiquitous environment under the guidance of Mark Weiser. Ubiquitous computing integrates the computers in the physical world to enhance human activities. In ubiquitous computing environment many interconnected computers having several interfaces will be used in the background to provide relevant services to the users intelligently. Ubiquitous computing applications, like ubiquitous health care service, ubiquitous shopping complex, ubiquitous tourist guide systems, ubiquitous learning systems, provide adaptive, user-centric, context-aware services intelligently in healthcare, product purchase, tourism and education fields respectively. The underlying network which provides uninterrupted connectivity for Unodes in different technology-based subnetworks is called as ubiquitous network. The objective of the work is to design solutions to the following issues in ubiquitous networks: monitoring ubiquitous application nodes, allocating resources to them, maintaining uniformly their QoS demand, and automatic service provision, in the ubiquitous networks. To solve the above-mentioned issues in ubiquitous network which consists of heterogeneous subnetworks and devices, we used agent technology as agents have the capability to take decisions by themselves on behalf of the user, migrate from device to device, and dynamically resolve the local problems. A node monitoring protocol monitors the health condition of a node by supervising the resource parameters, like data rate, delay, energy and throughput, as well as events, such as node failure, network failure and fault in the network. We have proposed a method to monitor the health condition and behaviour of a Unode (i.e., nodes running a ubiquitous application) in a ubiquitous network using static agent (SA) and mobile agent (MA). The MAs follow the Unode by migrating to the subnetwork (where the Unode is about to migrate), collect network utilization information of the Unode, and provide the higher level of information to the SA by analysing the raw network information, which reduces the network traffic and also workload of the main monitoring system. The past behaviour of the applications and networks, and history of the Unode and the predecessors are taken into consideration to help SA to take appropriate decision during the time of emergency situations, like unavailability of resources at the local administration, and to predict the migration of the Unode based on the node history. It is difficult to perform resource allocation for a Unode with the agreed Quality of Service (QoS) requirement in a ubiquitous network, which consists of subnetwork segments of different technologies with different resource constraints and control. We have proposed a priority-based resource allocation scheme for the Unodes in a ubiquitous network. The protocol exploits the advantages of both Static and Mobile Agents, by deploying them in different subnetworks (as and when required) to help the local administration to provide required network resources to the Unodes, and to ensure that the Unodes get the required network resources—by continuously monitoring their resource utilization and taking proactive actions. The resources are allocated fairly, by the SA in the subnetwork where the Unode has started availing the service and by MAs in other sub networks based on the priority values assigned to the Unodes. The priorities of the Unodes are calculated—by considering the importance of the application running on them, their resource utilization history and the cost effectiveness of the resource.ccc A ubiquitous application needs QoS guarantee to provide the required services to its users efficiently. The ubiquitous applications demand QoS as per the current environment context. Providing QoS in a ubiquitous network is a challenging task as the ubiquitous network consists of subnetworks of different technologies and controls. We have proposed a QoS architecture framework to guarantee the promised QoS requirements of an application running in a subnetwork of a ubiquitous network. The proposed architecture uses agents to predict the QoS requirements of applications running on a Unode by using the context information and history of the Unode and the subnetwork. The framework communicates with the local administration to allocate resources to the ubiquitous application running node. We have simulated the proposed framework in a ubiquitous network consisting several subnetworks. We have also modelled the proposed QoS architecture to analyse the average service time of different applications running on Unodes; and the effect of background load, i.e., nodes running the local applications, on Unodes. In a ubiquitous computing environment, a ubiquitous application provides personalized and adaptive services to a user. Web services paradigm provides the advantages of building distributed ubiquitous applications; hence, will be a better choice to be used by ubiquitous search mechanism to select and provide services, without any query setting, to the users as per their context. As the number of web services increases exponentially, selecting and providing the appropriate service among the vast number of required services become very difficult. Hence, to search the most relevant service, a correct query needs to be formulated. We have proposed a ubiquitous user query generation scheme for web services which helps the ubiquitous computing application to fetch and provide the most relevant web services to the users, at anyplace, anytime and on any device, by considering the context and profile information of the user, and history of search queries made by the users. In summary, we have developed; 1) a ubiquitous node monitoring protocol which monitors the health condition of a node and the network resources utilization in different subnetworks of the ubiquitous network; 2) a resource allocation scheme, which distributes the available resources at a local administration among the contending Unodes; 3) a QoS support, which maintains the QoS requirements of each Unode by negotiating with the local administrations of different subnetworks; 4) A ubiquitous user query model, which queries the services automatically and fetches the information on behalf of the user. We simulated our proposed protocols and schemes in different ubiquitous simulation environments. The results obtained in simulation shows the importance of the approaches and the efficiency of the proposed protocols and schemes.
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Madeira, Rui Miguel Neves Gonçalves. "Model-driven Personalisation of Human-Computer Interaction across Ubiquitous Computing Applications." Doctoral thesis, 2017. http://hdl.handle.net/10362/30072.

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Personalisation is essential to Ubiquitous Computing (Ubicomp), which focuses on a human-centred paradigm aiming to provide interaction with adaptive content, services, and interfaces towards each one of its users, according to the context of the applications’ scenarios. However, the provision of that appropriated personalised interaction is a true challenge due to different reasons, such as the user interests, heterogeneous environments and devices, dynamic user behaviour and data capture. This dissertation focuses on a model-driven personalisation solution that has the main goal of facili-tating the implementation of a personalised human-computer interaction across different Ubicomp scenarios and applications. The research reported here investigates how a generic and interoperable model for personalisation can be used, shared and processed by different applications, among diverse devices, and across different scenarios, studying how it can enrich human-computer interaction. The research started by the definition of a consistent user model with the integration of context to end in a pervasive model for the definition of personalisations across different applications. Besides the model proposal, the other key contributions within the solution are the modelling frame-work, which encapsulates the model and integrates the user profiling module, and a cloud-based platform to pervasively support developers in the implementation of personalisation across different applications and scenarios. This platform provides tools to put end users in control of their data and to support developers through web services based operations implemented on top of a personalisa-tion API, which can also be used independently of the platform for testing purposes, for instance. Several Ubicomp applications prototypes were designed and used to evaluate, at different phases, both the solution as a whole and each one of its components. Some were specially created with the goal of evaluating specific research questions of this work. Others were being developed with a pur-pose other than for personalisation evaluation, but they ended up as personalised prototypes to better address their initial goals. The process of applying the personalisation model to the design of the latter should also work as a proof of concept on the developer side. On the one hand, developers have been probed with the implementation of personalised applications using the proposed solution, or a part of it, to assess how it works and can help them. The usage of our solution by developers was also important to assess how the model and the platform respond to the developers’ needs. On the other hand, some prototypes that implement our model-driven per-sonalisation solution have been selected for end user evaluation. Usually, user testing was conducted at two different stages of the development, using: (1) a non-personalised version; (2) the final per-sonalised version. This procedure allowed us to assess if personalisation improved the human-com-puter interaction. The first stage was also important to know who were the end users and gather interaction data to come up with personalisation proposals for each prototype. Globally, the results of both developers and end users tests were very positive. Finally, this dissertation proposes further work, which is already ongoing, related to the study of a methodology to the implementation and evaluation of personalised applications, supported by the development of three mobile health applications for rehabilitation.
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Blumendorf, Marco [Verfasser]. "Multimodal interaction in smart environments : a model-based runtime system for ubiquitous user interfaces / vorgelegt von Marco Blumendorf." 2009. http://d-nb.info/997036575/34.

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Books on the topic "Ubiquitous User Query Model"

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McMullen, Bronagh. E-Com: The design of a personal communication assistant based on the ubiquitous computing model, which allows the user portability and connectivity. [S.l.]: [The author], 1996.

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Mukhtarov, Farhad, and Katherine A. Daniell. Transfer, Diffusion, Adaptation, and Translation of Water Policy Models. Edited by Ken Conca and Erika Weinthal. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199335084.013.30.

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Intensive cross-border movement of policy models is ubiquitous in the water sector. Examples include Integrated Water Resources Management (IWRM), Water User Associations (WUAs), and River Basin Organizations (RBOs), which have traveled around the world. However, despite the spread of global water policy models and their potential importance for sustainable development, scholars have struggled to develop adequate accounts of this process. To bridge this gap, we examine the extant analytical and methodological tools to study the movement of water policy models. We focus on the fit between a policy model and the context, the micro-politics of knowledge translation, and the inherent contingencies involved in water policy. Having recognized these obstacles, we offer some ways of conceptualizing the movement of water policy models. We illustrate each approach with vignettes from around the world.
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Book chapters on the topic "Ubiquitous User Query Model"

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Behrenbruch, Kay, Matthias Söllner, Michaela Schuldt, and Ludger Schmidt. "User Model." In Socio-technical Design of Ubiquitous Computing Systems, 59–70. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05044-7_4.

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Cena, Federica, and Roberto Furnari. "A Model for Feature-Based User Model Interoperability on the Web." In Advances in Ubiquitous User Modelling, 37–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-05039-8_3.

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Yigitbas, Enes, Silas Grün, Stefan Sauer, and Gregor Engels. "Model-Driven Context Management for Self-adaptive User Interfaces." In Ubiquitous Computing and Ambient Intelligence, 624–35. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67585-5_61.

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Yang, Jie, Lei Shu, Xiaoling Wu, Jinsung Cho, Sungyoung Lee, and Sangman Han. "ETRI-QM: Reward Oriented Query Model for Wireless Sensor Networks." In Embedded and Ubiquitous Computing – EUC 2005, 597–608. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11596356_60.

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Afzal, Muhammad, Maqbool Hussain, Taqdir Ali, Wajahat Ali Khan, Sungyoung Lee, and Byeong Ho Kang. "MLM-Based Automated Query Generation for CDSS Evidence Support." In Ubiquitous Computing and Ambient Intelligence. Personalisation and User Adapted Services, 296–99. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13102-3_49.

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Miñón, Raúl, Julio Abascal, Amaia Aizpurua, Idoia Cearreta, Borja Gamecho, and Nestor Garay. "Model-Based Accessible User Interface Generation in Ubiquitous Environments." In Human-Computer Interaction – INTERACT 2011, 572–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23768-3_85.

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Martínez-Villaseñor, Ma Lourdes, Luis Miralles-Pechuan, and Miguel González-Mendoza. "Interoperability in Electronic Health Records Through the Mediation of Ubiquitous User Model." In Ubiquitous Computing and Ambient Intelligence, 191–200. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48746-5_19.

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Jin, Fusheng, Zhendong Niu, Quanxin Zhang, Haiyang Lang, and Kai Qin. "A User Reputation Model for DLDE Learning 2.0 Community." In Digital Libraries: Universal and Ubiquitous Access to Information, 61–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89533-6_7.

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Bang, Green, and Ilju Ko. "A User Empirical Context Model for a Smart Home Simulator." In Advances in Computer Science and Ubiquitous Computing, 555–60. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-3023-9_85.

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Martínez Casas, David, Sebastián Villarroya Fernández, Moisés Vilar Vidal, José Manuel Cotos Yáñez, José Ramón Ríos Viqueira, and José Angel Taboada González. "Common Data Model in AmI Environments." In Ubiquitous Computing and Ambient Intelligence. Personalisation and User Adapted Services, 212–15. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13102-3_35.

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Conference papers on the topic "Ubiquitous User Query Model"

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Kharitonov, Eugene, Craig Macdonald, Pavel Serdyukov, and Iadh Ounis. "User model-based metrics for offline query suggestion evaluation." In SIGIR '13: The 36th International ACM SIGIR conference on research and development in Information Retrieval. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2484028.2484041.

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Wang, Xiaochun, and Yuanchun Shi. "UMDD: User Model Driven Software Development." In 2008 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing (EUC). IEEE, 2008. http://dx.doi.org/10.1109/euc.2008.59.

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Sanghoon Lee and Saeid Belkasim. "Poster: User-centered query expansion model for health disparities research." In 2013 IEEE 3rd International Conference on Computational Advances in Bio and Medical Sciences (ICCABS). IEEE, 2013. http://dx.doi.org/10.1109/iccabs.2013.6629211.

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Ahn, Jae-wook, and Peter Brusilovsky. "From User Query to User Model and Back: Adaptive Relevance-Based Visualization for Information Foraging." In IEEE/WIC/ACM International Conference on Web Intelligence (WI'07). IEEE, 2007. http://dx.doi.org/10.1109/wi.2007.80.

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Ahn, Jae-wook, and Peter Brusilovsky. "From User Query to User Model and Back: Adaptive Relevance-Based Visualization for Information Foraging." In IEEE/WIC/ACM International Conference on Web Intelligence (WI'07). IEEE, 2007. http://dx.doi.org/10.1109/wi.2007.4427177.

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Zhang, Yong, ShenSheng Zhang, SongQiao Han, and HongXia Tong. "User-Centric Service Provision Model for Adaptive Ubiquitous Computing Applications." In 2006 IEEE International Conference on Systems, Man and Cybernetics. IEEE, 2006. http://dx.doi.org/10.1109/icsmc.2006.384473.

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Park, Bokyoung, HyeonGyu Min, Green Bang, and Ilju Ko. "The User Activity Reasoning Model Based on Context-Awareness in a Virtual Living Space." In Ubiquitous Science and Engineering 2015. Science & Engineering Research Support soCiety, 2014. http://dx.doi.org/10.14257/ijdta.2015.86.13.

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Park, Bokyoung, HyeonGyu Min, Green Bang, and Ilju Ko. "The User Activity Reasoning Model Based on Context-Awareness in a Virtual Living Space." In Ubiquitous Science and Engineering 2015. Science & Engineering Research Support soCiety, 2015. http://dx.doi.org/10.14257/astl.2015.86.13.

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Wei, Cuncun, Chongben Huang, and Hengsong Tan. "A Personalized Model for Ontology-driven User Profiles Mining." In 2009 International Symposium on Intelligent Ubiquitous Computing and Education, IUCE. IEEE, 2009. http://dx.doi.org/10.1109/iuce.2009.128.

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Zuo, Yayao, Zhengwei Liu, Yang Zhou, Minghao Zhan, and Peilin Zhan. "Query-Specific Temporal Knowledge Graph Representation Learning Model." In 2022 IEEE Smartworld, Ubiquitous Intelligence & Computing, Scalable Computing & Communications, Digital Twin, Privacy Computing, Metaverse, Autonomous & Trusted Vehicles (SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta). IEEE, 2022. http://dx.doi.org/10.1109/smartworld-uic-atc-scalcom-digitaltwin-pricomp-metaverse56740.2022.00190.

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