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Social Network Analysis and Mining
Erschienen in: Social Network Analysis and Mining 4/2013

01.12.2013 | Original Article

Social recommendation: a review

verfasst von: Jiliang Tang, Xia Hu, Huan Liu

Erschienen in: Social Network Analysis and Mining | Ausgabe 4/2013

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Abstract

Recommender systems play an important role in helping online users find relevant information by suggesting information of potential interest to them. Due to the potential value of social relations in recommender systems, social recommendation has attracted increasing attention in recent years. In this paper, we present a review of existing recommender systems and discuss some research directions. We begin by giving formal definitions of social recommendation and discuss the unique property of social recommendation and its implications compared with those of traditional recommender systems. Then, we classify existing social recommender systems into memory-based social recommender systems and model-based social recommender systems, according to the basic models adopted to build the systems, and review representative systems for each category. We also present some key findings from both positive and negative experiences in building social recommender systems, and research directions to improve social recommendation capabilities.
Vorheriger Artikel Fast recommendation on bibliographic networks with sparse-matrix ordering and partitioning
Nächster Artikel A learning method for Top-N recommendations with incomplete data

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Fußnoten
16
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Metadaten
Titel
Social recommendation: a review
verfasst von
Jiliang Tang
Xia Hu
Huan Liu
Publikationsdatum
01.12.2013
Verlag
Springer Vienna
Erschienen in
Social Network Analysis and Mining / Ausgabe 4/2013
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-013-0141-9

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