Community detection in social recommender systems: a survey

Information extracted from social network services promise to improve the accuracy of recommender systems in various domains. Against this background, community detection techniques help us understand more of users’ collective behavior by clustering similar users w.r.t. their interests, preferences...

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Veröffentlicht in:Applied intelligence (Dordrecht, Netherlands) Netherlands), 2021-06, Vol.51 (6), p.3975-3995
Hauptverfasser: Gasparetti, Fabio, Sansonetti, Giuseppe, Micarelli, Alessandro
Format: Artikel
Sprache:eng
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Zusammenfassung:Information extracted from social network services promise to improve the accuracy of recommender systems in various domains. Against this background, community detection techniques help us understand more of users’ collective behavior by clustering similar users w.r.t. their interests, preferences and activities. The purpose of this paper is to bring the novice or practitioner quickly up to date with the main outcomes and research directions in the field of social recommendation based on community detection. The research synthesis consists of a narrative review which identifies what has been written on the topic of community-based recommender system. The comprehensive search of relevant literature aims at synthesizing prior study findings by identifying approaches that follow similar paradigms and techniques. The paper is of value to those involved with recommender systems and social media.
ISSN:0924-669X
1573-7497
DOI:10.1007/s10489-020-01962-3