Relevant bibliographies by topics / Personalization

Academic literature on the topic 'Personalization'

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Published: 4 June 2021
Last updated: 15 June 2024

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Journal articles on the topic "Personalization"

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Kaneko, Kazuki, Yusuke Kishita, and Yasushi Umeda. "Conducting Personalization Design Workshops — Designing Personalization Procedures." Procedia CIRP 98 (2021): 494–99. http://dx.doi.org/10.1016/j.procir.2021.01.140.

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Foshee, Cecile M., and Brian C. Nelson. "Avatar Personalization." International Journal of Gaming and Computer-Mediated Simulations 6, no. 2 (April 2014): 1–14. http://dx.doi.org/10.4018/ijgcms.2014040101.

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The authors explored the influence of avatar personalization on students' competence beliefs in a virtual world-based assessment environment. The avatar personalization options allowed seventh and eighth grade students (n = 110) to customize the appearance of their avatar and provided them with the option to personalize their in-world conversations by choosing a name for their avatar. Based on self-determination theory the authors hypothesized that the personalization in a virtual-world environment would influence students' motivation to engage by stimulating their situational interest and enable positive competence beliefs and deeper engagement. The results indicated that personalization stimulated situational interest and situational interest significantly predicted competence beliefs. This research contributes to the body of literature on the personalization principle by extending this work to a virtual environment. The findings highlight the importance of addressing students' affective needs and illustrate the value of interest; which can potentially influence students' attitudes towards testing and towards science.
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Adomavicius, Gediminas, and Alexander Tuzhilin. "Personalization technologies." Communications of the ACM 48, no. 10 (October 2005): 83–90. http://dx.doi.org/10.1145/1089107.1089109.

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Kim, Chin-Woo. "Price Personalization." LAW RESEARCH INSTITUTE CHUNGBUK NATIONAL UNIVERSITY 13, no. 2 (December 31, 2022): 43–81. http://dx.doi.org/10.34267/cbstl.2022.13.2.43.

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Product prices are now one of the many areas of our daily life in which artificial intelligence is becoming increasingly important. Digitization, especially online trading, opens up completely new possibilities and gives price adjustments a big boost in various ways. Thanks to their computing speed, algorithms can not only change and vary prices very quickly. Their enormous capacities for collecting and processing information even make it possible to include consumer data in the price calculation and thus adjust prices individually. Although we have become accustomed to uniform prices, the price has never been a purely static construct. Fluctuating prices are not a new phenomenon. Pricing freedom prevails within the framework of private autonomy. The aim of this paper is to examine how Korean law can respond to the new challenges posed by algorithmic price diversity. The law currently seems to offer little help against the currently existing lack of transparency in relation to the pricing process, which can go hand in hand with automated price individualization. So far, there are no legal regulations for disclosing how prices are determined. A central concern when dealing with individualized prices concerns the existence of information asymmetries and the (in)transparency of pricing strategies.
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Li, Cong. "When does web-based personalization really work? The distinction between actual personalization and perceived personalization." Computers in Human Behavior 54 (January 2016): 25–33. http://dx.doi.org/10.1016/j.chb.2015.07.049.

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Schreiber, Kristin L., and Jochen D. Muehlschlegel. "Personalization over Protocolization." Anesthesiology 134, no. 3 (January 19, 2021): 363–65. http://dx.doi.org/10.1097/aln.0000000000003695.

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Ono, Akinori. "Customization and Personalization." Japan Marketing Journal 40, no. 1 (June 30, 2020): 3–5. http://dx.doi.org/10.7222/marketing.2020.030.

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Rodrigues, Luiz, Paula T. Palomino, Armando M. Toda, Ana C. T. Klock, Wilk Oliveira, Anderson P. Avila-Santos, Isabela Gasparini, and Seiji Isotani. "Personalization Improves Gamification." Proceedings of the ACM on Human-Computer Interaction 5, CHI PLAY (October 5, 2021): 1–25. http://dx.doi.org/10.1145/3474714.

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Personalization of gamification is an alternative to overcome the shortcomings of the one-size-fits-all approach, but the few empirical studies analyzing its effects do not provide conclusive results. While many user and contextual information affect gamified experiences, prior personalized gamification research focused on a single user characteristic/dimension. Therefore, we hypothesize if a multidimensional approach for personalized gamification, considering multiple (user and contextual) information, can improve user motivation when compared to the traditional implementation of gamification. In this paper, we test that hypothesis through a mixed-methods sequential explanatory study. First, 26 participants completed two assessments using one of the two gamification designs and self-reported their motivations through the Situational Motivation Scale. Then, we conducted semi-structured interviews to understand learners' subjective experiences during these assessments. As result, the students using the personalized design were more motivated than those using the one-size-fits-all approach regarding intrinsic motivation and identified regulation. Furthermore, we found the personalized design featured game elements suitable to users' preferences, being perceived as motivating and need-supporting. Thus, informing i) practitioners on the use of a strategy for personalizing gamified educational systems that is likely to improve students' motivations, compared to OSFA gamification, and ii) researchers on the potential of multidimensional personalization to improve single-dimension strategies. For transparency, dataset and analysis procedures are available at https://osf.io/grzhp.
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Schneider, Hanna, Florian Lachner, Malin Eiband, Ceenu George, Purvish Shah, Chinmay Parab, Anjali Kukreja, Heinrich Hussmann, and Andreas Butz. "Privacy and personalization." Interactions 25, no. 3 (April 23, 2018): 52–55. http://dx.doi.org/10.1145/3197571.

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Volokh, Eugene. "Personalization and privacy." Communications of the ACM 43, no. 8 (August 2000): 84–88. http://dx.doi.org/10.1145/345124.345155.

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Dissertations / Theses on the topic "Personalization"

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Elbassuoni, Shady. "Adaptive personalization of web search : task sensitive approach to search personalization /." Saarbrücken : VDM Verlag Dr. Müller, 2008. http://d-nb.info/988664186/04.

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Almerfors, Mattias. "Visualization of Personalization Information." Thesis, Linköpings universitet, Institutionen för teknik och naturvetenskap, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-97829.

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There has been an increasing use of Internet as an information source and also as a new channel for business-to-business and business-to-consumer communication. This has lead to an increasing need for understanding web traffic and especially a growing need for analyzing this traffic, which demands new analysis tools. The objective for this study was to create an application framework for visualizing XML-formatted data representing web traffic reports. Visualization in two dimensions is created by using Batik, a Java ™ toolkit with the purpose of transforming a well formed XML document into a SVG document and then transcode this into an image format supported by today’s web browsers. Visualization in three dimensions is created by using the Java3D API. In order to create an aesthetically well-balanced graph in three dimensions representing a model of the web traffic on a site, the framework uses a layout algorithm called Graphical Embedder (GEM). This is a force-directed algorithm which uses physical analogy to model the graph. GEM emphasises the spring force approach combined with simulated annealing and the detection of oscillations and rotations. The design of the framework is built up using J2EE techniques. At the front-end this application framework uses JSP and Applet showing the graph for a customer using this service. At the back-end the framework uses Servlets combined with a Filter.
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Asif, Muhammad. "Personalization of Mobile Services." Doctoral thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-25576.

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The mobile era is well established and the number of smartphone users is showing exponential growth. The capability of smartphones and enabling technologies is also increasing and has opened many possibilities of personalized mobile services. The goal of personalization is to support the user by providing the right service at the rightmoment. Early focus of personalization was on content adaptations in different information systems. The new approaches of personalization are still needed for mobileservices as it is a compelling feature of mobile communication systems for both endusers and service providers.Personalization is providing a means of fulfilling users’ needs more effectively andefficiently and, consequently increasing users’ satisfaction. By providing successfulpersonalization, a high degree of user satisfaction and a pleasant user experience can beachieved. Some features of personalization can cause problems and may outweigh thebenefits of personalization.This thesis has focused on how to achieve scrutable mobile client-side personalizationwhile keeping the user’s privacy. The issue of privacy in personalization of mobileservices can be reduced by shifting the control of their personal information towards theusers. Our research goal is to understand and improve the personalization process anddevelop an architecture for scrutable mobile client-side personalization while keepingthe user s’ privacy. Moreover, there is a need to develop an evaluation framework tomeasure the effectiveness of mobile services personalization. A design science researchmethodology is adopted in this research work. More particular contributions of thethesis are as follows: C1: Identifications of the research issues and challenges in personalization of mobileservices. C2: An approach for delivering personalized mobile services. C3: Development of mobile client-side personalization architecture. C4: Development of mobile services Personalization Evaluation Model. C5: Identification of the prospects of scrutable personalization of mobile services.
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Donnelly, Christopher. "Enhancing Personalization Within ASSISTments." Digital WPI, 2015. https://digitalcommons.wpi.edu/etd-theses/249.

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ASSISTments is an online adaptive tutoring system with the ability to provide assistance to students in the form of hints and scaffolding. ASSISTments has many features to help students improve their knowledge. Researchers run studies in order to discover ways for students to learn better but ASSISTments is missing one major aspect for researchers: student level personalization. It is easy to create an assignment for a particular class or school but it would take much longer to create an assignment for each student and it would be difficult for the teacher to look through many assignment reports. One of the strongest code blocks in coding is the if-then; allowing the program to branch off to another set of code under certain circumstances. ASSISTments needed an if-then system in order for students to branch off to other parts of the assignment under certain circumstances. With this, researchers would be able to personalize assignments to give more help to lower knowledge students or allow students to get a choice of what kind of tutoring they would like to receive. With this idea in mind, the basic if-then structure was implemented into ASSISTments using problem or problem set correctness as the condition statement. Once the if-then system was created opportunities opened to create additional experiments and run studies in ASSISTments. The basic if-then was limited in using correctness only for its condition statement. This meant that a new if-then system would need to be implemented to include custom condition statements that allowed the researcher to have the assignment branch on any condition using all the information recorded in the assignment. While work was being done on the if-then system, research was being done and two papers were written on partial credit in ASSISTments. Partial credit was found out to be as accurate as knowledge tracing in determining student performance on the next problem. Once a partial credit algorithm was found, a study using if-then was analyzed. It was found that there was no statistically significant difference between students who were given a choice on their feedback and students who received no choice.
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Yang, Yanwu. "Towards spatial web personalization." Paris, ENSAM, 2006. https://pastel.archives-ouvertes.fr/pastel-00002481.

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La mise à disposition d'information et de services spatiaux a récemment proliféré sur le web dans la mesure où la plupart de nos activités quotidiennes sont géo-réferencées. Les communautés d'utilisateurs de services spatiaux sur le web sont de plus larges et variées, en constante expansion et transformation avec une augmentation constante des gammes d'applications proposées. Cette profusion d'applications entraîne un nombre important de problématiques de recherche, et notamment celles liées à l'identification des intérêts et des préférences de l'utilisateur, afin d'adapter les services délivrés aux besoins du client. Cette recherche propose une architecture intégrée de modélisation de profils d'utilisateur et d'approximation de leurs préférences, et de mise à disposition de services personnalisés orientés vers l'information spatiale. L'architecture proposée se compose d'un service de personnalisation et d'un modèle sémantique orienté utilisateur. Ces deux composants communiquent des informations sur l'utilisateur par des processus interactifs. Ce service de personalisation est basé sur trois principes : la mémoire associative neurale bi-directionnelle, des mesures contextuelles et spatiales orientées-utilisateur de proximité et de similarité, des schémas d'image et des concepts d'affordance. Ces concepts sont implémentés à partir d'une interface utilisateur qui intègre les différents composants identifiés, et offre un éventail de stratégies personnalisées de recherche, et un moteur hybride de personnalisation. Le modèle d'utilisateur utilise des logiques expressives de description pour caractériser les différentes catégories d'utilisateur, afin d'adapter les besoins d'utilisateur aux exigences d'une application. Un scénario dans le domaine du tourisme et un prototype Java réalisent une validation expérimentale de notre recherche à partir de techniques de personnalisation
In the past few years, spatial information and services have proliferated on the Web, due to the fact that most of our daily activities are related to the spatial dimension. The user communities involved in spatial web services are essentially diverse, still in an expansion and transformation with constantly increasing number of user and applications. This opens many research challenges, such as the elicitation of user's interests and preferences and customization of information services on the spatial Web. This PhD research proposes an integrated framework for user modeling and preference elicitation, and personalization services on the spatial Web. The framework identifies personalization services and a semantic user model for spatial web applications. These two components communicate information and knowledge about the user through inter-process communications. The personalization services are based on three mechanisms: the Bi-directional Neural Associative Memory, user-centric spatial proximity and similarity measures, image schemata and affordance concepts. A web-based user interface is integrated with these components, and offers a spectrum of personalized search strategies and a hybrid personalization engine. The user model employs expressive description logics to describe assumptions about the user and to infer implicit user features from user's descriptions as required by an application system. An application scenario in the tourism domain and a Web-based Java prototype provide an experimental validation of the research framework and identified personalization techniques
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Boutet, Antoine. "Decentralizing news personalization systems." Thesis, Rennes 1, 2013. http://www.theses.fr/2013REN1S023/document.

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L'évolution rapide du web a changé la façon dont l'information est créée, distribuée, évaluée et consommée. L'utilisateur est dorénavant mis au centre du web en devenant le générateur de contenu le plus prolifique. Pour évoluer dans le flot d'informations, les utilisateurs ont besoin de filtrer le contenu en fonction de leurs centres d'intérêts. Pour bénéficier de contenus personnalisés, les utilisateurs font appel aux réseaux sociaux ou aux systèmes de recommandations exploitant leurs informations privées. Cependant, ces systèmes posent des problèmes de passage à l'échelle, ne prennent pas en compte la nature dynamique de l'information et soulèvent de multiples questions d'un point de vue de la vie privée. Dans cette thèse, nous exploitons les architectures pair-à-pair pour implémenter des systèmes de recommandations pour la dissémination personnalisée des news. Une approche pair-à-pair permet un passage à l'échelle naturel et évite qu'une entité centrale contrôle tous les profils des utilisateurs. Cependant, l'absence de connaissance globale fait appel à des schémas de filtrage collaboratif qui doivent palier les informations partielles et dynamiques des utilisateurs. De plus, ce schéma de filtrage doit pouvoir respecter la vie privée des utilisateurs. La première contribution de cette thèse démontre la faisabilité d'un système de recommandation de news totalement distribué. Le système proposé maintient dynamiquement un réseau social implicit pour chaque utilisateur basé sur les opinions qu'il exprime à propos des news reçues. Les news sont disséminées au travers d'un protocole épidémique hétérogène qui (1) biaise l'orientation des cibles et (2) amplifie la dissémination de chaque news en fonction du niveau d'intérêt qu'elle suscite. Ensuite, pour améliorer la vie privée des utilisateurs, nous proposons des mécanismes d'offuscation permettant de cacher le profil exact des utilisateurs sans trop dégrader la qualité de la recommandation fournie. Enfin, nous explorons un nouveau modèle tirant parti des avantages des systèmes distribués tout en conservant une architecture centralisée. Cette solution hybride et générique permet de démocratiser les systèmes de recommandations en offrant aux fournisseurs de contenu un système de personnalisation à faible coût
The rapid evolution of the web has changed the way information is created, distributed, evaluated and consumed. Users are now at the center of the web and becoming the most prolific content generators. To effectively navigate through the stream of available news, users require tools to efficiently filter the content according to their interests. To receive personalized content, users exploit social networks and recommendation systems using their private data. However, these systems face scalability issues, have difficulties in coping with interest dynamics, and raise a multitude of privacy challenges. In this thesis, we exploit peer-to-peer networks to propose a recommendation system to disseminate news in a personalized manner. Peer-to-peer approaches provide highly-scalable systems and are an interesting alternative to Big brother type companies. However, the absence of any global knowledge calls for collaborative filtering schemes that can cope with partial and dynamic interest profiles. Furthermore, the collaborative filtering schemes must not hurt the privacy of users. The first contribution of this thesis conveys the feasibility of a fully decentralized news recommender. The proposed system constructs an implicit social network based on user profiles that express the opinions of users about the news items they receive. News items are disseminated through a heterogeneous gossip protocol that (1) biases the orientation of the dissemination, and (2) amplifies dissemination based on the level of interest in each news item. Then, we propose obfuscation mechanisms to preserve privacy without sacrificing the quality of the recommendation. Finally, we explore a novel scheme leveraging the power of the distribution in a centralized architecture. This hybrid and generic scheme democratizes personalized systems by providing an online, cost-effective and scalable architecture for content providers at a minimal investment cost
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Hoang, Van Tieng. "Measuring Web Search Personalization." Thesis, IMT Alti Studi Lucca, 2018. http://e-theses.imtlucca.it/246/1/Hoang_phdthesis.pdf.

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Personalization in online services is the practice of tailoring data contents for customers according to what is supposed to be their expectation. By design, personalization has been considered an important tool to help users to find the most interesting relevant data. By doing that, personalization also filters the web contents and potentially narrows the view of users. In this context, our work aims to measure personalization levels of web search results. First, we study personalization for web search engines with two case studies about Google Search. The results show a remarkable level of Google personalized search results based on sets of keywords, and we show that a specific website appears as prevalent in the results of web searches. Second, we measure the personalization degrees of an online news aggregator to provide a wider view of the problems. It also shows that compelling evidence such as “suggested for you" heavily depends on past users’ activities. Finally, we study personalization of search results on an online shopping platformby measuring price steering phenomenon. Particularly, we investigate the impacts of online behaviours, locations and economic performance factors, and we observe that price steering is based on user’s behaviours but it is also influenced by the geographic location of users.
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SONG, Songbo. "Advanced personalization of IPTV services." Phd thesis, Institut National des Télécommunications, 2012. http://tel.archives-ouvertes.fr/tel-00814620.

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Internet Protocol TV (IPTV) delivers television content to users over IP-based network. Different from the traditional TV services, IPTV platforms provide users with large amount of multimedia contents with interactive and personalized services, including the targeted advertisement, on-demand content, personal video recorder, and so on. IPTV is promising since it allows to satisfy users experience and presents advanced entertainment services. On the other hand, the Next Generation Network (NGN) approach in allowing services convergence (through for instance coupling IPTV with the IP Multimedia Subsystem (IMS) architecture or NGN Non-IMS architecture) enhances users' experience and allows for more services personalization. Although the rapid advancement in interactive TV technology (including IPTV and NGN technologies), services personalization is still in its infancy, lacking the real distinguish of each user in a unique manner, the consideration of the context of the user (who is this user, what is his preferences, his regional area, location, ..) and his environment (characteristics of the users' devices 'screen types, size, supported resolution, '' and networks available network types to be used by the user, available bandwidth, ..') as well as the context of the service itself (content type and description, available format 'HD/SD', available language, ..) in order to provide the adequate personalized content for each user. This advanced IPTV services allows services providers to promote new services and open new business opportunities and allows network operators to make better utilization of network resources through adapting the delivered content according to the available bandwidth and to better meet the QoE (Quality of Experience) of clients. This thesis focuses on enhanced personalization for IPTV services following a user-centric context-aware approach through providing solutions for: i) Users' identification during IPTV service access through a unique and fine-grained manner (different from the identification of the subscription which is the usual current case) based on employing a personal identifier for each user which is a part of the user context information. ii) Context-Aware IPTV service through proposing a context-aware system on top of the IPTV architecture for gathering in a dynamic and real-time manner the different context information related to the user, devices, network and service. The context information is gathered throughout the whole IPTV delivery chain considering the user domain, network provider domain, and service/content provider domain. The proposed context-aware system allows monitoring user's environment (devices and networks status), interpreting user's requirements and making the user's interaction with the TV system dynamic and transparent. iii) Personalized recommendation and selection of IPTV content based on the different context information gathered and the personalization decision taken by the context-aware system (different from the current recommendation approach mainly based on matching content to users' preferences) which in turn highly improves the users' Quality of Experience (QoE) and enriching the offers of IPTV services
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Song, Xiang Ph D. Massachusetts Institute of Technology. "Personalization of future urban mobility." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120637.

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Thesis: Ph. D. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 91-97).
In the past few years, we have been experiencing rapid growth of new mobility solutions fueled by a myriad of innovations in technologies such as automated vehicles and in business models such as shared-ride services. The emerging mobility solutions are often required to be profitable, sustainable, and efficient while serving heterogeneous needs of mobility consumers. Given high-resolution consumer mobility behavior collected from smartphones and other GPS-enabled devices, the operational management strategies for future urban mobility can be personalized and serve for various system objectives. This thesis focuses on the personalization of future urban mobility through the personalized menu optimization model. The model built upon individual consumer's choice behavior generates a personalized menu for app-based mobility solutions. It integrates behavioral modeling of consumer mobility choice with optimization objectives. Individual choice behavior is modeled through logit mixture and the parameters are estimated with a hierarchical Bayes (HB) procedure. In this thesis, we first present an enhancement to HB procedure with alternative priors for covariance matrix estimation in order to improve the estimation performance. We also evaluate the benefits of personalization through a Boston case study based on real travel survey data. In addition, we present a sequential personalized menu optimization algorithm that addresses trade-off between exploration (learn uncertain demand of menus) and exploitation (offer the best menu based on current knowledge). We illustrate the benefits of exploration under different conditions including different types of heterogeneity.
by Xiang Song.
Ph. D. in Transportation
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Li, Andrew A. (Andrew Andi). "Algorithms for large-scale personalization." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119351.

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Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 191-205).
The term personalization typically refers to the activity of online recommender systems, and while product and content personalization is now ubiquitous in e-commerce, systems today remain relatively primitive: they are built on a small fraction of available data, run with heuristic algorithms, and restricted to e-commerce applications. This thesis addresses key challenges and new applications for modern, large-scale personalization. In particular, this thesis is outlined as follows: First, we formulate a generic, flexible framework for learning from matrix-valued data, including the kinds of data commonly collected in e-commerce. Underlying this framework is a classic de-noising problem called tensor recovery, for which we provide an efficient algorithm, called Slice Learning, that is practical for massive datasets. Further, we establish near-optimal recovery guarantees that represent an order improvement over the best available results for this problem. Experimental results from a music recommendation platform are shown. Second, we apply this de-noising framework to new applications in precision medicine where data are routinely complex and in high dimensions. We describe a simple, accurate proteomic blood test (a 'liquid biopsy') for cancer detection that relies on de-noising via the Slice Learning algorithm. Experiments on plasma from healthy patients that were later diagnosed with cancer demonstrate that our test achieves diagnostically significant sensitivities and specificities for many types of cancers in their earliest stages. Third, we present an efficient, principled approach to operationalizing recommendations, i.e. the decision of exactly what items to recommend. Motivated by settings such as online advertising where the space of items is massive and recommendations must be made in milliseconds, we propose an algorithm that simultaneously achieves two important properties: (1) sublinear runtime and (2) a constant-factor guarantee under a wide class of choice models. Our algorithm relies on a new sublinear time sampling scheme, which we develop to solve a class of problems that subsumes the classic nearest neighbor problem. Results from a massive online content recommendation firm are given. Fourth, we address the problem of cost-effectively executing a broad class of computations on commercial cloud computing platforms, including the computations typically done in personalization. We formulate this as a resource allocation problem and introduce a new approach to modeling uncertainty - the Data-Driven Prophet Model - that treads the line between stochastic and adversarial modeling, and is amenable to the common situation where stochastic modeling is challenging, despite the availability of copious historical data. We propose a simple, scalable algorithm that is shown to be order-optimal in this setting. Results from experiments on a commercial cloud platform are shown.
by Andrew A. Li.
Ph. D.
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Books on the topic "Personalization"

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Mandai, Masaki, ed. Personalization in Gynecologic Oncology. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4711-7.

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Carberry, Sandra, Stephan Weibelzahl, Alessandro Micarelli, and Giovanni Semeraro, eds. User Modeling, Adaptation, and Personalization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38844-6.

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Houben, Geert-Jan, Gord McCalla, Fabio Pianesi, and Massimo Zancanaro, eds. User Modeling, Adaptation, and Personalization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02247-0.

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Tanaka, Yuzuru, Nicolas Spyratos, Tetsuya Yoshida, and Carlo Meghini, eds. Information Search, Integration and Personalization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40140-4.

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Flouris, Giorgos, Dominique Laurent, Dimitris Plexousakis, Nicolas Spyratos, and Yuzuru Tanaka, eds. Information Search, Integration, and Personalization. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44900-1.

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Konstan, Joseph A., Ricardo Conejo, José L. Marzo, and Nuria Oliver, eds. User Modeling, Adaption and Personalization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22362-4.

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Masthoff, Judith, Bamshad Mobasher, Michel C. Desmarais, and Roger Nkambou, eds. User Modeling, Adaptation, and Personalization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31454-4.

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Grant, Emanuel, Dimitris Kotzinos, Dominique Laurent, Nicolas Spyratos, and Yuzuru Tanaka, eds. Information Search, Integration, and Personalization. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-43862-7.

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De Bra, Paul, Alfred Kobsa, and David Chin, eds. User Modeling, Adaptation, and Personalization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13470-8.

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Ricci, Francesco, Kalina Bontcheva, Owen Conlan, and Séamus Lawless, eds. User Modeling, Adaptation and Personalization. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20267-9.

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Book chapters on the topic "Personalization"

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Shekhar, Shashi, and Hui Xiong. "Personalization." In Encyclopedia of GIS, 855. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_973.

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Fraser, Stephen R. G. "Personalization." In Real-World ASP.NET: Building a Content Management System, 57–76. Berkeley, CA: Apress, 2002. http://dx.doi.org/10.1007/978-1-4302-0832-7_4.

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Glasby, Jon, and Helen Dickinson. "Personalization." In A–Z of Inter-Agency Working, 137–41. London: Macmillan Education UK, 2014. http://dx.doi.org/10.1007/978-1-137-00533-5_48.

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Lorenz, Patrick A. "Personalization." In ASP.NET 2.0 Revealed, 177–98. Berkeley, CA: Apress, 2004. http://dx.doi.org/10.1007/978-1-4302-0791-7_7.

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Wicklund, Phil. "Experience Personalization." In Practical Sitecore 8 Configuration and Strategy, 79–105. Berkeley, CA: Apress, 2015. http://dx.doi.org/10.1007/978-1-4842-1236-3_3.

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Koutrika, Georgia. "Data Personalization." In Data-Centric Systems and Applications, 213–34. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20062-0_11.

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Mylonas, Phivos, and Yannis Avrithis. "Multimedia Personalization." In Encyclopedia of Multimedia, 588–89. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-78414-4_50.

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Fensel, Dieter, Borys Omelayenko, Ying Ding, Michel Klein, Alan Flett, Ellen Schulten, Guy Botquin, Mike Brown, and Gloria Dabiri. "Information Personalization." In Intelligent Information Integration in B2B Electronic Commerce, 57–63. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-5538-1_6.

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Schulte, Stephanie Ricker. "22. Personalization." In Digital Keywords, edited by Benjamin Peters, 242–55. Princeton: Princeton University Press, 2016. http://dx.doi.org/10.1515/9781400880553-024.

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Block, Howard, Rob Castle, and David Hritz. "Personalization Services." In Creating Web Portals with BEA WebLogic, 445–79. Berkeley, CA: Apress, 2003. http://dx.doi.org/10.1007/978-1-4302-0764-1_13.

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Conference papers on the topic "Personalization"

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Blom, Jan. "Personalization." In CHI '00 extended abstracts. New York, New York, USA: ACM Press, 2000. http://dx.doi.org/10.1145/633292.633483.

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Lee, Min Kyung, Junsung Kim, Jodi Forlizzi, and Sara Kiesler. "Personalization revisited." In the 2015 ACM International Joint Conference. New York, New York, USA: ACM Press, 2015. http://dx.doi.org/10.1145/2750858.2807552.

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Xiao, Wenyi, Huan Zhao, Haojie Pan, Yangqiu Song, Vincent W. Zheng, and Qiang Yang. "Beyond Personalization." In KDD '19: The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3292500.3330965.

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Rey, Stéphanie, Celia Picard, Pierre Mauriéras, and Anke Brock. "Personalization totem." In IHM '18: 30e Conférence Francophone sur l'Interaction Homme-Machine. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3286689.3286715.

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Oinas-Kukkonen, Harri. "Personalization Myopia." In Mindtrek 2018: Academic Mindtrek 2018. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3275116.3275121.

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Miao, Xu, Chun-Te Chu, Lijun Tang, Yitong Zhou, Joel Young, and Anmol Bhasin. "Distributed Personalization." In KDD '15: The 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2783258.2788626.

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van Setten, Mark, Sean M. McNee, and Joseph A. Konstan. "Beyond personalization." In the 10th international conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1040830.1040839.

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Kuhl, Juliane, and Dieter Krause. "Identifying Potentials of Product Personalization." In ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/detc2022-88463.

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Abstract Adapting components and modules within the context of product personalization promises exact fulfillment of individual customer requirements. However, personalization should only be used where it is valuable and manageable. The design of product architectures with personalizable modules has so far received little methodological support. Therefore, a method for personalization-oriented product design is to be developed in the long term. In a first step, it is important to systematically derive potentials for personalization, which can then be examined in terms of value and workload. The aim of this paper is to identify indicators that promote personalization. Additionally, it will be presented how these indications could be applied for a product family. Based on an analysis of the aim of personalization as well as research on variety indicators in the literature and a comprehensive analysis of product families where personalization is already applied, personalization indicators are derived. Personalization is particularly relevant where engineer-to-order solutions are used before, for components already having a high variety and where fit and appearance play a role. With the help of an adapted Module Interface Graph (MIG), the analysis results can be documented and visualized in order to derive personalization potentials. Thus, the approach presented in this article represents a significant element of personalization-oriented product architecture design.
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Majumder, Anirban, and Nisheeth Shrivastava. "Know your personalization." In the 22nd international conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2488388.2488464.

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Kobsa, Alfred, Ramnath K. Chellappa, and Sarah Spiekermann. "Privacy-enhanced personalization." In CHI '06 extended abstracts. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1125451.1125749.

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Reports on the topic "Personalization"

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Aldrich, Susan. Agilent's Virtuous Circle of Personalization. Boston, MA: Patricia Seybold Group, August 2013. http://dx.doi.org/10.1571/cs08-08-13cc.

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Aldrich, Susan. Peerius Recommendation and Personalization Solution Evaluation. Boston, MA: Patricia Seybold Group, June 2012. http://dx.doi.org/10.1571/pr06-21-12cc.

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Marienko, Maiia V., Yulia H. Nosenko, and Mariya P. Shyshkina. Personalization of learning using adaptive technologies and augmented reality. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4418.

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The research is aimed at developing the recommendations for educators on using adaptive technologies and augmented reality in personalized learning implementation. The latest educational technologies related to learning personalization and the adaptation of its content to the individual needs of students and group work are considered. The current state of research is described, the trends of development are determined. Due to a detailed analysis of scientific works, a retrospective of the development of adaptive and, in particular, cloud-oriented systems is shown. The preconditions of their appearance and development, the main scientific ideas that contributed to this are analyzed. The analysis showed that the scientists point to four possible types of semantic interaction of augmented reality and adaptive technologies. The adaptive cloud-based educational systems design is considered as the promising trend of research. It was determined that adaptability can be manifested in one or a combination of several aspects: content, evaluation and consistency. The cloud technology is taken as a platform for integrating adaptive learning with augmented reality as the effective modern tools to personalize learning. The prospects of the adaptive cloud-based systems design in the context of teachers training are evaluated. The essence and place of assistive technologies in adaptive learning systems design are defined. It is shown that augmented reality can be successfully applied in inclusive education. The ways of combining adaptive systems and augmented reality tools to support the process of teachers training are considered. The recommendations on the use of adaptive cloud-based systems in teacher education are given.
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Sedova, Katerina, Christine McNeill, Aurora Johnson, Aditi Joshi, and Ido Wulkan. AI and the Future of Disinformation Campaigns: Part 2: A Threat Model. Center for Security and Emerging Technology, December 2021. http://dx.doi.org/10.51593/2021ca011.

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Artificial intelligence offers enormous promise to advance progress and powerful capabilities to disrupt it. This policy brief is the second installment of a series that examines how advances in AI could be exploited to enhance operations that automate disinformation campaigns. Building on the RICHDATA framework, this report describes how AI can supercharge current techniques to increase the speed, scale, and personalization of disinformation campaigns.
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Sarofim, Samer. Developing an Effective Targeted Mobile Application to Enhance Transportation Safety and Use of Active Transportation Modes in Fresno County: The Role of Application Design & Content. Mineta Transportation Institute, July 2021. http://dx.doi.org/10.31979/mti.2021.2013.

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This research empirically investigates the need for, and the effective design and content of, a proposed mobile application that is targeted at pedestrians and cyclists in Fresno County. The differential effect of the proposed mobile app name and colors on the target audience opinions was examined. Further, app content and features were evaluated for importance and the likelihood of use. This included design appeal, attractiveness, relevance, ease of navigation, usefulness of functions, personalization and customization, message recipients’ attitudes towards message framing, and intended behaviors related to pedestrian, cyclist, and motorist traffic safety practices. Design mobile application features tested included image aesthetics, coherence and organization, and memorability and distinction. Potential engagement with the mobile app was assessed via measuring the users’ perceived enjoyment while using the app. The behavioral intentions to adopt the app and likelihood to recommend the app were assessed. The willingness to pay for purchasing the app was measured. This research provided evidence that a mobile application designed for pedestrians and cyclists is needed, with high intentions for its adoption. Functions, such as Safety Information, Weather Conditions, Guide to Trails, Events for Walkers and Bikers, and Promotional Offers are deemed important by the target population. This research was conducted in an effort to increase active transportation mode utilization and to enhance the safety of vulnerable road users. The public, city administrators, transportation authorities, and policy makers shall benefit from the results of this study by adapting the design and the features that are proposed in this research and were found appealing and useful for the target vulnerable road user groups. The need of the proposed mobile application and its main functions are established, based on the results of this research, which propagates further steps of implementation by city administrators and transportation authorities.
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Osadchyi, Viacheslav V., Hanna B. Varina, Kateryna P. Osadcha, Olha V. Kovalova, Valentyna V. Voloshyna, Oleksii V. Sysoiev, and Mariya P. Shyshkina. The use of augmented reality technologies in the development of emotional intelligence of future specialists of socionomic professions under the conditions of adaptive learning. CEUR Workshop Proceedings, July 2020. http://dx.doi.org/10.31812/123456789/4633.

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In modern conditions, innovative augmented reality technologies are actively developing, which are widespread in many areas of human activity. Introduction of advanced developments in the process of professional training of future specialists of socionomic professions in the conditions of adaptive training, contributes to the implementation of the principles of a personalized approach and increase the overall level of competitiveness. The relevant scientific article is devoted to the theoretical and empirical analysis result of conducting a psychodiagnostic study on an innovative computer complex HC-psychotest. of the features of the implementation of augmented reality technologies in the construct of traditional psychological and pedagogical support aimed at the development of emotional intelligence of the future specialist. The interdisciplinary approach was used while carrying out the research work at the expense of the general fund of the state budget: “Adaptive system for individualization and personalization of professional training of future specialists in the conditions of blended learning”. A comprehensive study of the implementation of traditional psychological-pedagogical and innovative augmented reality technologies was conducted in the framework of scientific cooperation of STEAM-Laboratory, Laboratory of Psychophysiological Research and Laboratory of Psychology of Health in Bogdan Khmelnitsky Melitopol State Pedagogical University. The theoretical analysis considers the structural model of emotional intelligence of the future specialist of socionomic professions, which is represented by two structural components: intrapersonal construct of emotional intelligence and interpersonal construct of emotional intelligence. Each component mediates the inherent emotional intelligence of interpretive, regulatory, adaptive, stress-protective and activating functions. The algorithm of the empirical block of research is presented by two stages: ascertaining and forming research. According to the results of the statement, low indicators were found on most scales, reflecting the general level of emotional intelligence development of future specialists, actualizing the need to find and implement effective measures for the development of emotional intelligence components in modern higher education and taking into account information development and digitalization. As part of the formative stage of the research implementation, a comprehensive program “Development of emotional intelligence of future professionals” was tested, which integrated traditional psychological and pedagogical technologies and innovative augmented reality technologies. This program is designed for 24 hours, 6 thematic classes of 4 hours. According to the results of a comprehensive ascertaining and shaping research, the effectiveness of the influence of augmented reality technologies on the general index of emotional intelligence is proved. The step-by-step model of integration of augmented reality components influencing the ability to analyze, understand and regulate emotional states into a complex program of emotional intelligence development is demonstrated. According to the results of the formative study, there is a dominance of high indicators of the following components: intrapersonal (50%), interpersonal (53.3%). Thus, we can say that intrapersonal and interpersonal emotional intelligence together involve the actualization of various cognitive processes and skills, and are related to each other. Empirical data were obtained as a
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