Relevant bibliographies by topics / Contextual personalization

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Academic literature on the topic 'Contextual personalization'

Author: Grafiati

Published: 11 September 2021

Last updated: 1 February 2022

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Journal articles on the topic "Contextual personalization"

Zhang, Chuxu, Huaxiu Yao, Lu Yu, Chao Huang, Dongjin Song, Haifeng Chen, Meng Jiang, and Nitesh V. Chawla. "Inductive Contextual Relation Learning for Personalization." ACM Transactions on Information Systems 39, no. 3 (May 22, 2021): 1–22. http://dx.doi.org/10.1145/3450353.

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Web personalization, e.g., recommendation or relevance search, tailoring a service/product to accommodate specific online users, is becoming increasingly important. Inductive personalization aims to infer the relations between existing entities and unseen new ones, e.g., searching relevant authors for new papers or recommending new items to users. This problem, however, is challenging since most of recent studies focus on transductive problem for existing entities. In addition, despite some inductive learning approaches have been introduced recently, their performance is sub-optimal due to relatively simple and inflexible architectures for aggregating entity’s content. To this end, we propose the inductive contextual personalization (ICP) framework through contextual relation learning. Specifically, we first formulate the pairwise relations between entities with a ranking optimization scheme that employs neural aggregator to fuse entity’s heterogeneous contents. Next, we introduce a node embedding term to capture entity’s contextual relations, as a smoothness constraint over the prior ranking objective. Finally, the gradient descent procedure with adaptive negative sampling is employed to learn the model parameters. The learned model is capable of inferring the relations between existing entities and inductive ones. Thorough experiments demonstrate that ICP outperforms numerous baseline methods for two different applications, i.e., relevant author search and new item recommendation.

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Afzal, Muhammad, Syed Imran Ali, Rahman Ali, Maqbool Hussain, Taqdir Ali, Wajahat Ali Khan, Muhammad Bilal Amin, Byeong Ho Kang, and Sungyoung Lee. "Personalization of wellness recommendations using contextual interpretation." Expert Systems with Applications 96 (April 2018): 506–21. http://dx.doi.org/10.1016/j.eswa.2017.11.006.

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Kim, Nam Young, and S. Shyam Sundar. "Personal Relevance Versus Contextual Relevance." Journal of Media Psychology 24, no. 3 (January 2012): 89–101. http://dx.doi.org/10.1027/1864-1105/a000067.

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Personalization, or the tailoring of content to meet users’ unique needs, is considered a desirable feature of digital media, particularly websites, because it results in content that is highly relevant to the user. However, it is not always possible to provide personally relevant content. Under such circumstances, the best that a system can do is provide contextually relevant peripheral content (e.g., ads) based on the topic of the main content (e.g., search-engine output). This raises an important question: Does context relevance have the same positive effects on user perceptions of websites as personal relevance? If context relevance can indeed make up for the lack of personalization, then boosting it via ad content on the site should serve to enhance appeal even when the main content is not personalized. Using a 2 × 2 factorial experiment (N = 60), we investigated whether perceptions of a website and the ads themselves varied as a function of the presence of personalized site content and ad relevance to website context. Results indicate that personal relevance and context relevance are fungible in contributing to user attitudes toward the site. Theoretical and practical implications are discussed.

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Moore, Philip T., and Hai V. Pham. "Personalization and rule strategies in data-intensive intelligent context-aware systems." Knowledge Engineering Review 30, no. 2 (March 2015): 140–56. http://dx.doi.org/10.1017/s0269888914000265.

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AbstractThe concept of personalization in its many forms has gained traction driven by the demands of computer-mediated interactions generally implemented in large-scale distributed systems and ad hoc wireless networks. Personalization requires the identification and selection of entities based on a defined profile (a context); an entity has been defined as a person, place, or physical or computational object. Context employs contextual information that combines to describe an entities current state. Historically, the range of contextual information utilized (in context-aware systems) has been limited to identity, location, and proximate data; there has, however, been advances in the range of data and information addressed. As such, context can be highly dynamic with inherent complexity. In addition, context-aware systems must accommodate constraint satisfaction and preference compliance.This article addresses personalization and context with consideration of the domains and systems to which context has been applied and the nature of the contextual data. The developments in computing and service provision are addressed with consideration of the relationship between the evolving computing landscape and context. There is a discussion around rule strategies and conditional relationships in decision support. Logic systems are addressed with an overview of the open world assumption versus the closed world assumption and the relationship with the Semantic Web. The event-driven rule-based approach, which forms the basis upon which intelligent context processing can be realized, is presented with an evaluation and proof-of-concept. The issues and challenges identified in the research are considered with potential solutions and research directions; alternative approaches to context processing are discussed. The article closes with conclusions and open research questions.

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Sun, Xu, and Andrew May. "The role of spatial contextual factors in mobile personalization at large sports events." Personal and Ubiquitous Computing 13, no. 4 (June 27, 2008): 293–302. http://dx.doi.org/10.1007/s00779-008-0203-6.

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Horodenko, Lesya. "Contexts of the Network Communication’s Origin." Current Issues of Mass Communication, no. 16 (2014): 16–25. http://dx.doi.org/10.17721/2312-5160.2014.16.16-25.

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The article represents a research of the scientific and theoretical backgrounds of the “network communication” phenomenon, and identifies the contextual relations of network communication in various fields of science. This study examines how information and communication technologies – mobile phones, social networking websites, blogging, instant messaging, and etc. – impacted on formation of theoretical concepts of network communication. We believe that a limited set of technologies promoted a variety of traditional parameters of communication researches. Internet activity and social networks encouraged the personalization of mass communication. We substantiate that the emphasis on the new media in the process of network personalization constitutes the basic context of genesis of network communication. The networks with persistent and pervasive nature of new technologies are more diversified than they have ever been before.

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Palalas, Agnieszka, and Norine Wark. "A Framework for Enhancing Mobile Learner-Determined Language Learning in Authentic Situational Contexts." International Journal of Computer-Assisted Language Learning and Teaching 10, no. 4 (October 2020): 83–97. http://dx.doi.org/10.4018/ijcallt.2020100106.

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Mobile technology melds the mobile learner's authentic real and virtual worlds, enabling increasingly untethered personalized, learner-determined language learning opportunities. This article introduces an evidence-based framework founded upon cumulative findings from a number of the authors' recent and ongoing research projects. This framework provides guidance for designing mobile language learning activities within the learner's evolving personal, authentic situational learning context. The framework consists of three learner dimensions and four external contextual affordances that synergistically define the dynamics of this learning context. The merger of these dimensions and external contextual elements yields three interdependent learning concepts—personalization, adaptation, and relevancy—which enhance the mobile learner's motivation and self-determination. Application of these concepts enables instructors and learners to design mobile language activities that consider the interplay of numerous factors impacting language learning in context.

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MYLONAS, PH, D. VALLET, P. CASTELLS, M. FERNÁNDEZ, and Y. AVRITHIS. "Personalized information retrieval based on context and ontological knowledge." Knowledge Engineering Review 23, no. 1 (March 2008): 73–100. http://dx.doi.org/10.1017/s0269888907001282.

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AbstractContext modeling has long been acknowledged as a key aspect in a wide variety of problem domains. In this paper we focus on the combination of contextualization and personalization methods to improve the performance of personalized information retrieval. The key aspects in our proposed approach are (1) the explicit distinction between historic user context and live user context, (2) the use of ontology-driven representations of the domain of discourse, as a common, enriched representational ground for content meaning, user interests, and contextual conditions, enabling the definition of effective means to relate the three of them, and (3) the introduction of fuzzy representations as an instrument to properly handle the uncertainty and imprecision involved in the automatic interpretation of meanings, user attention, and user wishes. Based on a formal grounding at the representational level, we propose methods for the automatic extraction of persistent semantic user preferences, and live, ad-hoc user interests, which are combined in order to improve the accuracy and reliability of personalization for retrieval.

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Behlol, Malik, and Mohammad Kaini. "Comparative Effectiveness of Contextual and Structural Method of Teaching Vocabulary." English Language Teaching 4, no. 1 (February 28, 2011): 90. http://dx.doi.org/10.5539/elt.v4n1p90.

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The study was conducted to find out effectiveness of contextual an, structural method of teaching vocabulary in English at secondary level. It was an experimental study in which the pretest posttest design was used. The population of the study was the students of secondary classes studying in Government secondary schools of Rawalpindi District. Purposive and random sampling was applied to select the school and subjects. The significance of difference between the scores of groups at 0.05 level was tested applying t test. The study revealed that the contextual method is more useful for high achievers (HA) whereas structural method is more useful for average and low achievers. The HA performed better with the contextual method due to study of words in different contexts and taking help from contextual clues that has prompted spoken and written fluency. Better performance of the average and low achievers with the structural method was due to the morphological analyses of a word, role of the students as the partner in the learning process, generation and active processing of vocabulary, provision of multiple exposure of different intensity for practice and personalization of word learning.

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Manrique-Sancho, María-Teresa, Silvania Avelar, Teresa Iturrioz-Aguirre, and Miguel-Ángel Manso-Callejo. "Using the Spatial Knowledge of Map Users to Personalize City Maps: A Case Study with Tourists in Madrid, Spain." ISPRS International Journal of Geo-Information 7, no. 8 (August 20, 2018): 332. http://dx.doi.org/10.3390/ijgi7080332.

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The aim of personalized maps is to help individual users to read maps and focus on the most task-relevant information. Several approaches have been suggested to develop personalized maps for cities, but few consider the spatial knowledge of its users. We propose the design of “cognitively-aware” personalized maps, which take into account the previous experience of users in the city and how the urban space is configured in their minds. Our aim is to facilitate users’ mental links between maps and city places, stimulating users to recall features of the urban space and to assimilate new spatial knowledge. To achieve this goal, we propose the personalization of maps through a map design process based on user modeling and on inferring personalization guidelines from hand-drawn sketches of urban spaces. We applied this process in an experiment with tourists in Madrid, Spain. We categorized the participants into three types of tourists—“Guided”, “Explorer”, and “Conditioned”—according to individual and contextual factors that can influence their spatial knowledge of the city. We also extracted design guidelines from tourists’ sketches and developed map prototypes. The empirical results seem to be promising for developing personalized city maps that could be produced on-the-fly in the future.

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Dissertations / Theses on the topic "Contextual personalization"

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

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

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Agbele, Kehinde Kayode. "Context-awareness for adaptive information retrieval systems." Thesis, University of the Western Cape, 2014. http://hdl.handle.net/11394/3845.

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Philosophiae Doctor - PhD
This research study investigates optimization of IRS to individual information needs in order of relevance. The research addressed development of algorithms that optimize the ranking of documents retrieved from IRS. In this thesis, we present two aspects of context-awareness in IR. Firstly, the design of context of information. The context of a query determines retrieved information relevance. Thus, executing the same query in diverse contexts often leads to diverse result rankings. Secondly, the relevant context aspects should be incorporated in a way that supports the knowledge domain representing users’ interests. In this thesis, the use of evolutionary algorithms is incorporated to improve the effectiveness of IRS. A context-based information retrieval system is developed whose retrieval effectiveness is evaluated using precision and recall metrics. The results demonstrate how to use attributes from user interaction behaviour to improve the IR effectiveness

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Ferreira, José Pedro Santos. "Online shopping behavior in offline retail stores : strategic value for companies?" Master's thesis, 2015. http://hdl.handle.net/10400.14/18791.

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In a world where e-tailing and traditional in-store shopping live together and complement each other in several shopping activities (Chu, et. al, 2010), little is known about the possibility of an emerging reality in which online and offline shopping merge into one single phenomenon. The purpose of this dissertation is to explore whether consumers are willing to engage in a shopping behavior inside retail stores in a way that is similar to the one they have when shopping online. Additionally, it sheds light on the strategic value the online-offline shopping holds. To accomplish these objectives, a smartphone shopping scenario is designed to represent a situation that enables consumers to perform in-store shopping tasks in a digital manner, mixing and enhancing the features and benefits of e-tailing with traditional retail store experience. Moreover, a research model, that includes preliminary assumptions and eleven hypotheses to be tested, is designed to fundament the research methodology used. Based on this research model and the smartphone shopping scenario, a survey is conducted in order to collect empirical data on customer’s appraisal of the online-offline shopping process as well as their availability to permit recording their shopping data obtained after performing shopping tasks via smartphone. Furthermore, to access the strategic value of the online-offline shopping process, Resource-based View theory is used in order to identify the existence of possible sources of sustainable competitive advantage. The findings from the research show that respondents value the characteristics of the online-offline shopping process as well as they are willing to permit recording their own shopping data so that they are able to benefit from a contextual personalized shopping experience while shopping in traditional retail stores. The dissertation concludes that because customers value the characteristics of the online-offline shopping process they have a strong motivation to engage in an online-offline shopping behavior. Moreover, since they are willing to trade their shopping privacy for a contextual personalized shopping experience, it is plausible to admit that a strategy based on contextual personalization has potential to be strategic for retail companies. In fact, to generate such a strategy, the customer knowledge generated in the process is argued to be a firm resource that, combined with dynamic capabilities to leverage its utility in providing a contextual personalization experience, is considered to be a source of sustainable competitive advantage meaning the online-offline process has potential to be strategic to retail firms.

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Book chapters on the topic "Contextual personalization"

Chen, Guanliang, and Li Chen. "Recommendation Based on Contextual Opinions." In User Modeling, Adaptation, and Personalization, 61–73. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08786-3_6.

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Walczak, Krzysztof, Jakub Flotyński, and Dominik Strugała. "Semantic Contextual Personalization of Virtual Stores." In Lecture Notes in Computer Science, 220–36. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25965-5_17.

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Goffart, Klaus, Michael Schermann, Christopher Kohl, Jörg Preißinger, and Helmut Krcmar. "Towards Identifying Contextual Factors on Parking Lot Decisions." In User Modeling, Adaptation, and Personalization, 320–25. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08786-3_28.

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Odić, Ante. "Detecting, Acquiring and Exploiting Contextual Information in Personalized Services." In User Modeling, Adaptation, and Personalization, 374–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31454-4_39.

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Kramár, Tomáš. "Towards Contextual Search: Social Networks, Short Contexts and Multiple Personas." In User Modeling, Adaption and Personalization, 434–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22362-4_45.

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Codina, Victor, Francesco Ricci, and Luigi Ceccaroni. "Exploiting the Semantic Similarity of Contextual Situations for Pre-filtering Recommendation." In User Modeling, Adaptation, and Personalization, 165–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38844-6_14.

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Fernández-Tobías, Ignacio. "Mining Semantic Data, User Generated Contents, and Contextual Information for Cross-Domain Recommendation." In User Modeling, Adaptation, and Personalization, 371–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38844-6_42.

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Baker, Ryan S. J. d., Albert T. Corbett, Sujith M. Gowda, Angela Z. Wagner, Benjamin A. MacLaren, Linda R. Kauffman, Aaron P. Mitchell, and Stephen Giguere. "Contextual Slip and Prediction of Student Performance after Use of an Intelligent Tutor." In User Modeling, Adaptation, and Personalization, 52–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13470-8_7.

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do Carmo, Ricardo R. M., and Marco A. Casanova. "An Architecture for Dynamic Contextual Personalization of Multimedia Narratives in IoT Environments." In Advances in Intelligent Systems and Computing, 502–21. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52246-9_36.

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Otebolaku, Abayomi Moradeyo, and Maria Teresa Andrade. "Context-Aware Personalization for Mobile Services." In Encyclopedia of Information Science and Technology, Fourth Edition, 6031–42. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2255-3.ch524.

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Audiovisual content consumption on mobile platforms is rising exponentially and this trend will continue in the next years as mobile devices become more sophisticated. Thus, smartphones are gradually replacing our desktops as they increasingly become cheaper and more powerful with excellent multimedia processing support. As mobile users go about their routines, they continuously browse the Web, seeking interesting content to consume, and also uploading personal content. However, users encounter huge volume of content, that does not match their preferences, resulting in mobile information overload. Context-aware media personalization (CAMP) was proposed as a solution to this problem. CAMP assists users to select relevant content among alternatives considering users' preferences and contexts. This solution, however, are limited to static contexts. Our contribution is Mobile Context-Aware Media Personalization(MobCAMP), which is a special kind of personalization that utilizes user's contexts and activities to suggest media content according to the user's tastes and contextual situations.

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Conference papers on the topic "Contextual personalization"

Volkovs, Maksims, Anson Wong, Zhaoyue Cheng, Felipe Pérez, Ilya Stanevich, and Yichao Lu. "Robust contextual models for in-session personalization." In RecSys Challenge '19: ACM Recommender Systems Challenge 2019 Workshop. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3359555.3359558.

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Miele, Antonio, Elisa Quintarelli, Emanuele Rabosio, and Letizia Tanca. "ADaPT: Automatic Data Personalization based on contextual preferences." In 2014 IEEE 30th International Conference on Data Engineering (ICDE). IEEE, 2014. http://dx.doi.org/10.1109/icde.2014.6816749.

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Miele, Antonio, Elisa Quintarelli, and Letizia Tanca. "A methodology for preference-based personalization of contextual data." In the 12th International Conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1516360.1516394.

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Bendada, Walid, Guillaume Salha, and Théo Bontempelli. "Carousel Personalization in Music Streaming Apps with Contextual Bandits." In RecSys '20: Fourteenth ACM Conference on Recommender Systems. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3383313.3412217.

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Unger, Moshe, Bracha Shapira, Lior Rokach, and Ariel Bar. "Inferring Contextual Preferences Using Deep Auto-Encoding." In UMAP '17: 25th Conference on User Modeling, Adaptation and Personalization. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3079628.3079666.

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Al-Ghossein, Marie, Talel Abdessalem, and Anthony Barré. "Exploiting Contextual and External Data for Hotel Recommendation." In UMAP '18: 26th Conference on User Modeling, Adaptation and Personalization. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3213586.3225245.

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Welber, Sophie, Valerie Zhao, Claire Dolin, Olivia Morkved, Henry Hoffmann, and Blase Ur. "Do Users Have Contextual Preferencesfor Smartphone Power Management?" In UMAP '21: 29th ACM Conference on User Modeling, Adaptation and Personalization. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3450613.3456813.

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Kristoffersen, Miklas S., Sven E. Shepstone, and Zheng-Hua Tan. "A Dataset for Inferring Contextual Preferences of Users Watching TV." In UMAP '18: 26th Conference on User Modeling, Adaptation and Personalization. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3209219.3209263.

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Mylonas, Phivos. "A Fuzzy Contextual Approach Towards Intelligent Educational Content Adaptation." In Second International Workshop on Semantic Media Adaptation and Personalization (SMAP 2007). IEEE, 2007. http://dx.doi.org/10.1109/smap.2007.31.

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