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Enhancing Mutual Awareness in Group Recommender Systems

By Anthony Jameson, Stephan Baldes, and Thomas Kleinbauer (2003)

In B. Mobasher & S. S. Anand (Eds.), Proceedings of the IJCAI 2003 Workshop on Intelligent Techniques for Web Personalization. Menlo Park, CA: AAAI.

Abstract

An increasingly important type of recommender system comprises those that generate recommendations for groups rather than for individuals. The decision of a group member whether or not to accept a given recommendation can depend not only on her own evaluation of the content of the recommendation but also on her beliefs about the evaluations of the other group members and about their motivation (e.g., egocentric vs. cooperative). Yet this type of mutual awareness may be hard to achieve when group recommendations are delivered by a web-based system to group members who cannot communicate face-to-face. After introducing these issues on a general level, we discuss them more concretely by discussing a prototype group recommender system that uses several novel methods to enhance mutual awareness among group members, ranging from a group-oriented interface technique for specifying preferences to animated characters that serve as representatives of group members who are not currently available for communication.

Note

Workshop page: http://maya.cs.depaul.edu/~mobasher/itwp03/

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Paper:  [PDF File]

BibTeX entry

@incollection{JamesonBK03ITWP,
  year = {2003},
  author = {{Jameson}, Anthony and
            {Baldes}, Stephan and
            {Kleinbauer}, Thomas},
  editor = {{Mobasher}, Bamshad and
            {Anand}, Sarabjot S.},
  title = {Enhancing Mutual Awareness in Group Recommender Systems},
  booktitle = {{P}roceedings of the {IJCAI} 2003 {W}orkshop on {I}ntelligent {T}echniques for {W}eb
    {P}ersonalization},
  address = {Menlo Park, CA},
  publisher = {AAAI}}