Emotions in Context-Aware Recommender Systems

Chapter
Part of the Human–Computer Interaction Series book 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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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.College of Computing and Digital MediaDePaul UniversityChicagoUSA

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