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Using a Rich Context Model for a News Recommender System for Mobile Users
Linnaeus University, Faculty of Technology, Department of Media Technology.ORCID iD: 0000-0001-9062-1609
Linnaeus University, Faculty of Technology, Department of Media Technology.ORCID iD: 0000-0001-7072-1063
Linnaeus University, Faculty of Technology, Department of Media Technology. (CeLeKT)ORCID iD: 0000-0002-6937-345X
2014 (English)In: UMAP 2014 Extended Proceedings: Posters, Demos, Late-breaking Results and Workshop Proceedings of the 22nd Conference on User Modeling, Adaptation, and Personalization co-located with the 22nd Conference on User Modeling, Adaptation, and Personalization (UMAP2014) Aalborg, Denmark, July 7-11, 2014. / [ed] Iván Cantador, Min Chi, Rosta Farzan, Robert Jäschke, CEUR , 2014, Vol. 1181, p. 13-16Conference paper, Published paper (Refereed)
Abstract [en]

Recommender systems have become an important application domain related to the development of personalized mobile services. Thus, various recommender mechanisms have been developed for filtering and delivering relevant information to mobile users. This paper presents a rich context model to provide the relevant content of news to the current context of mobile users. The proposed rich context model allows not only providing relevant news with respect to the user’s current context but, at the same time, also determines a convenient representation format of news suitable for mobile devices.

Place, publisher, year, edition, pages
CEUR , 2014. Vol. 1181, p. 13-16
Series
CEUR Workshop Proceedings, ISSN 1613-0073 ; Vol 1181
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Media Technology
Identifiers
URN: urn:nbn:se:lnu:diva-34511Scopus ID: 2-s2.0-84925259973OAI: oai:DiVA.org:lnu-34511DiVA: diva2:720594
Conference
2nd International Workshop on News Recommendation and Analytics (NRA) in conjunction with 22nd Conference on User Modelling, Adaptation and Personalization (UMAP 2014), July 11, 2014, Åalberg
Available from: 2014-05-31 Created: 2014-05-31 Last updated: 2018-01-11Bibliographically approved
In thesis
1. A Rich Context Model: Design and Implementation
Open this publication in new window or tab >>A Rich Context Model: Design and Implementation
2017 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The latest developments of mobile devices include a variety of hardware features that allow for more rich data collection and services. Numerous sensors, Internet connectivity, low energy Bluetooth connectivity to other devices (e.g., smart watches, activity tracker, health data monitoring devices) are just some examples of hardware that helps to provide additional information that can be beneficially used for many application domains. Among others, they could be utilized in mobile learning scenarios (for data collection in science education, field trips), in mobile health scenarios (for health data collection and monitoring the health state of patients, changes in health conditions and/or detection of emergency situations), and in personalized recommender systems. This information captures the current context situation of the user that could help to make mobile applications more personalized and deliver a better user experience. Moreover, the context related information collected by the mobile device and the different applications can be enriched by using additional external information sources (e.g., Web Service APIs), which help to describe the user’s context situation in more details.

The main challenge in context modeling is the lack of generalization at the core of the model, as most of the existing context models depend on particular application domains or scenarios. We tackle this challenge by conceptualizing and designing a rich generic context model. In this thesis, we present the state of the art of recent approaches used for context modeling and introduce a rich context model as an approach for modeling context in a domain-independent way. Additionally, we investigate whether context information can enhance existing mobile applications by making them sensible to the user’s current situation. We demonstrate the reusability and flexibility of the rich context model in a several case studies. The main contributions of this thesis are: (1) an overview of recent, existing research in context modeling for different application domains; (2) a theoretical foundation of the proposed approach for modeling context in a domain-independent way; (3) several case studies in different mobile application domains.

Place, publisher, year, edition, pages
Växjö: Faculty of Technology, Linnaeus University, 2017. p. 103
Series
Reports: Linnaeus University, Faculty of Technology ; 48
Keyword
Context modeling, rich context model, mobile users, current context of the user, mobile sensors, multidimensional vector space model, contextualization
National Category
Computer Systems
Research subject
Computer and Information Sciences Computer Science, Media Technology
Identifiers
urn:nbn:se:lnu:diva-60850 (URN)978-91-88357-62-5 (ISBN)
Presentation
2017-02-17, C1202, Växjö, 09:15 (English)
Opponent
Supervisors
Available from: 2017-02-24 Created: 2017-02-22 Last updated: 2017-09-01Bibliographically approved

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