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Recommendation to Groups

  • Chapter
The Adaptive Web

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4321))

Abstract

Recommender systems have traditionally recommended items to individual users, but there has recently been a proliferation of recommenders that address their recommendations to groups of users. The shift of focus from an individual to a group makes more of a difference than one might at first expect. This chapter discusses the most important new issues that arise, organizing them in terms of four subtasks that can or must be dealt with by a group recommender: 1. acquiring information about the user’s preferences; 2. generating recommendations; 3. explaining recommendations; and 4. helping users to settle on a final decision. For each issue, we discuss how it has been dealt with in existing group recommender systems and what open questions call for further research.

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Author information

Authors and Affiliations

  1. DFKI, German Research Center for Artificial Intelligence,  

    Anthony Jameson

  2. Department of Computer Science, University College Dublin,  

    Barry Smyth

Authors
  1. Anthony Jameson
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  2. Barry Smyth
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Peter Brusilovsky Alfred Kobsa Wolfgang Nejdl

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Jameson, A., Smyth, B. (2007). Recommendation to Groups. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds) The Adaptive Web. Lecture Notes in Computer Science, vol 4321. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72079-9_20

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  • DOI: https://doi.org/10.1007/978-3-540-72079-9_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72078-2

  • Online ISBN: 978-3-540-72079-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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