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Emotions in Context-Aware Recommender Systems

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Book cover Emotions and Personality in Personalized Services

Part of the book series: Human–Computer Interaction Series ((HCIS))

Abstract

Recommender systems are decision aids that offer users personalized suggestions for products and other items. Context-aware recommender systems are an important subclass of recommender systems that take into account the context in which an item will be consumed or experienced. In context-aware recommendation research, a number of contextual features have been identified as important in different recommendation applications: such as companion in the movie domain, time and mood in the music domain, and weather or season in the travel domain. Emotions have also been demonstrated to be significant contextual factors in a variety of recommendation scenarios. In this chapter, we describe the role of emotions in context-aware recommendation, including defining and acquiring emotional features for recommendation purposes, incorporating such features into recommendation algorithms. We conclude with a sample evaluation , showing the utility of emotion in recommendation generation.

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Notes

  1. 1.

    Moviepilot, http://moviepilot.com/, this data set was the basis for the 1st Challenge on Context-Aware Movie Recommendation in ACM RecSys 2010, but it no longer being distributed.

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Author information

Authors and Affiliations

  1. College of Computing and Digital Media, DePaul University, 243 S Wabash Ave ST 400, Chicago, IL, 60604, USA

    Yong Zheng, Bamshad Mobasher & Robin Burke

Authors
  1. Yong Zheng
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  2. Bamshad Mobasher
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  3. Robin Burke
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Corresponding author

Correspondence to Yong Zheng .

Editor information

Editors and Affiliations

  1. Department of Computational Perception, Johannes Kepler University, Linz, Austria

    Marko TkalÄŤiÄŤ

  2. Department of Computer Science, University of Bari Aldo Moro, Bari, Italy

    Berardina De Carolis

  3. Department of Computer Science, University of Bari Aldo Moro, Bari, Italy

    Marco de Gemmis

  4. Preserje, Ljubljana, Slovenia

    Ante Odić

  5. Faculty of electrical engineering, University of Ljubljana, Ljubljana, Slovenia

    Andrej Košir

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Zheng, Y., Mobasher, B., Burke, R. (2016). Emotions in Context-Aware Recommender Systems. In: Tkalčič, M., De Carolis, B., de Gemmis, M., Odić, A., Košir, A. (eds) Emotions and Personality in Personalized Services. Human–Computer Interaction Series. Springer, Cham. https://doi.org/10.1007/978-3-319-31413-6_15

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  • DOI: https://doi.org/10.1007/978-3-319-31413-6_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-31411-2

  • Online ISBN: 978-3-319-31413-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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