Info-Bead group modeling in a mobile scenario
Pages 682 - 689
Abstract
The mobile scenario is an extremely challenging one when it comes to providing personalized, context aware services to mobile users. Users may dynamically and continuously enter and leave smart environments that may offer them relevant services. However, the environments may not know anything about the users and hence, providing personalized, context aware services becomes a challenge: users need to be identified, queried for their preferences and monitored before a service can be provided. The lack of standard, easy to use personalization infrastructure worsens the problem -- every service provider needs to build a proprietary, add-hoc user modeling component from scratch, thus to invest considerable effort in the task. This work builds on top of previous work on Info-Beads user modeling. Following past research, it suggests an Info-Beads approach for mobile user modeling for monitoring users and enabling standardization in building user models, reusing both components and data. The specific contribution is to allow monitoring mobile users, reasoning on their data and creating individual and group models from it. We demonstrate the ideas in the area of media content recommendations for groups and individual mobile users in smart environments, as a possible case study.
References
[1]
Agger, B. (2011). iTime: Labor and life in a smartphone era. Time & Society, 20(1), 119--136.
[2]
Ardissono, L., Console, L., & Torre, I. (2001). An adaptive system for the personalized access to news. AI Commun., 14(3), 129--147.
[3]
Ardissono, L., Goy, A., Petrone, G., Segnan, M., & Torasso, P. (2002). Tailoring the recommendation of tourist information to heterogeneous user groups. In Siegfried Reich, Manolis M. Tzagarakis, Paul M. E. De Bra (Ed.), Hypermedia: Openness, structural awareness, and adaptivity () Springer Berlin Heidelberg.
[4]
Dim, E., Kuflik, T., & Reinhartz-Berger, I. (2015). When user modeling intersects software engineering: The Info-Bead user modeling approach. User Modeling and User-Adapted Interaction, 1--41.
[5]
Doyle, G. (2010). From television to multi-platform less from more or more for less? Convergence: The International Journal of Research into New Media Technologies, 16(4), 431--449.
[6]
Finin, T., & Drager, D. (1986). GUMS: A general user modeling system. InProceedings of the Workshop on Strategic Computing Natural Language, 224--230. for Computational Linguistics
[7]
International Data Corporation (IDC). (2015). IDC worldwide quarterly mobile phone tracker, february 24, 2015.
[8]
Kobsa, A. (2001). Generic user modeling systems. User Modeling and User-Adapted Interaction, 11(1-2), 49--63.
[9]
Kuflik, T., Mumblat, Y. and Dim E. Enabling Mobile User Modeling Infrastructure for Personalization in Ubiquitous Computing. MobileSoft 2015 May 16th-17th, Firenze, Italy, co-located with ICSE 2015.
[10]
McCarthy, J. F., & Anagnost, T. D. (1998). MusicFX: An arbiter of group preferences for computer supported collaborative workouts. In Proceedings of the 1998 ACM Conference on Computer Supported Cooperative Work, (ACM) 363--372.
[11]
Ofcom. (2015). Adults' media use and attitudes report. (Report).Ofcom. Available online at: http://stakeholders.ofcom.org.uk/binaries/research/media-literacy/media-lit-10years/2015_Adults_media_use_and_attitudes_report.pdf
[12]
Perrault, C. R., Allen, J. F., & Cohen, P. R. (1978). Speech acts as a basis for understanding dialogue coherence. In Proceedings of the 1978 Workshop on Theoretical Issues in Natural Language Processing, 125--132. for Computational Linguistics
[13]
Rich, E. (1979). User modeling via stereotypes*. Cognitive Science, 3(4), 329--354.
[14]
Yu, Z., Zhou, X., Hao, Y., & Gu, J. (2006). TV program recommendation for multiple viewers based on user profile merging. User Modeling and User-Adapted Interaction, 16(1), 63--82.
Index Terms
- Info-Bead group modeling in a mobile scenario
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Published In
September 2016
664 pages
ISBN:9781450344135
DOI:10.1145/2957265
- General Chairs:
- Fabio Paternò,
- Kaisa Väänänen,
- Program Chairs:
- Karen Church,
- Jonna Häkkilä,
- Antonio Krüger,
- Marcos Serrano
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Published: 06 September 2016
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MobileHCI '16: 18th International Conference on Human-Computer Interaction with Mobile Devices and Services
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