Investigating serendipity in recommender systems based on real user feedback

Denis Kotkov, Joseph A. Konstan, Qian Zhao, Jari Veijalainen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Scopus citations

Abstract

Over the past several years, research in recommender systems has emphasized the importance of serendipity, but there is still no consensus on the definition of this concept and whether serendipitous items should be recommended is still not a well-addressed question. According to the most common definition, serendipity consists of three components: relevance, novelty and unexpectedness, where each component has multiple variations. In this paper, we looked at eight different definitions of serendipity and asked users how they perceived them in the context of movie recommendations. We surveyed 475 users of the movie recommender system, MovieLens regarding 2146 movies in total and compared those definitions of serendipity based on user responses. We found that most kinds of serendipity and all the variations of serendipity components broaden user preferences, but one variation of unexpectedness hurts user satisfaction. We found effective features for detecting serendipitous movies according to definitions that do not include this variation of unexpectedness. We also found that different variations of unexpectedness and different kinds of serendipity have different effects on preference broadening and user satisfaction. Among movies users rate in our system, up to 8.5% are serendipitous according to at least one definition of serendipity, while among recommendations that users receive and follow in our system, this ratio is up to 69%.

Original languageEnglish (US)
Title of host publicationProceedings of the 33rd Annual ACM Symposium on Applied Computing, SAC 2018
PublisherAssociation for Computing Machinery
Pages1341-1350
Number of pages10
ISBN (Electronic)9781450351911
DOIs
StatePublished - Apr 9 2018
Event33rd Annual ACM Symposium on Applied Computing, SAC 2018 - Pau, France
Duration: Apr 9 2018Apr 13 2018

Publication series

NameProceedings of the ACM Symposium on Applied Computing

Other

Other33rd Annual ACM Symposium on Applied Computing, SAC 2018
Country/TerritoryFrance
CityPau
Period4/9/184/13/18

Bibliographical note

Funding Information:
Œe research at the University of Jyväskylä was partially supported by the Academy of Finland, grant #268078 and the KAUTE Foundation.

Publisher Copyright:
© 2018 ACM.

Keywords

  • Novelty
  • Recommender systems
  • Relevance
  • Serendipity
  • Unexpectedness

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