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Group Recommender Systems pp 105–126Cite as

Explanations for Groups

Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Abstract

Explanations are used in recommender systems for various reasons. Users have to be supported in making (high-quality) decisions more quickly. Developers of recommender systems want to convince users to purchase specific items. Users should better understand how the recommender system works and why a specific item has been recommended. Users should also develop a more in-depth understanding of the item domain. Consequently, explanations are designed in order to achieve specific goals such as increasing the transparency of a recommendation or increasing a user’s trust in the recommender system. In this chapter, we provide an overview of existing research related to explanations in recommender systems, and specifically discuss aspects relevant to group recommendation scenarios. In this context, we present different ways of explaining and visualizing recommendations determined on the basis of aggregated predictions and aggregated models strategies.

Keywords

  • Group Recommendation Scenarios
  • Recommender Systems
  • Domain Items
  • Constraint-based Recommender
  • Content-based Filtering

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Alexander Felfernig, Nava Tintarev,Thi Ngoc Trang Tran, and Martin Stettinger

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Fig. 6.6

Notes

  1. 1.

    In contrast to single-user decision making, the exchange of decision-relevant knowledge among group members has to be fostered [4].

  2. 2.

    In line with Jameson and Smyth [32], we interpret arguments as elementary parts of explanations.

  3. 3.

    See also Chap. 3.

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Authors and Affiliations

  1. Institute for Software Technology, Graz University of Technology, Graz, Austria

    Alexander Felfernig & Martin Stettinger

  2. EURECAT, Centre Tecnológico de Catalunya, Barcelona, Spain

    Ludovico Boratto

  3. Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano, Italy

    Marko Tkalčič

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  1. Alexander Felfernig
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Felfernig, A., Boratto, L., Stettinger, M., Tkalčič, M. (2018). Explanations for Groups. In: Group Recommender Systems . SpringerBriefs in Electrical and Computer Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-75067-5_6

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