6533b7d6fe1ef96bd1265b0e
RESEARCH PRODUCT
Challenges of Serendipity in Recommender Systems
Jari VeijalainenDenis KotkovShuaiqiang Wangsubject
haasteet (ongelmat)ta113Computer scienceSerendipitysuosittelujärjestelmätserendipitychallenges02 engineering and technologyRecommender systemunexpectednessnoveltyevaluation metricsWorld Wide Webrelevanssi020204 information systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingrelevancerecommender systemsdescription
Most recommender systems suggest items similar to a user profile, which results in boring recommendations limited by user preferences indicated in the system. To overcome this problem, recommender systems should suggest serendipitous items, which is a challenging task, as it is unclear what makes items serendipitous to a user and how to measure serendipity. The concept is difficult to investigate, as serendipity includes an emotional dimension and serendipitous encounters are very rare. In this paper, we discuss mentioned challenges, review definitions of serendipity and serendipity-oriented evaluation metrics. The goal of the paper is to guide and inspire future efforts on serendipity in recommender systems. peerReviewed
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2016-01-01 | Proceedings of the 12th International Conference on Web Information Systems and Technologies |