article

Social tagging in recommender systems: a survey of the state-of-the-art and possible extensions

Authors:

Aleksandra Klasnja Milicevic,

Alexandros Nanopoulos,

Mirjana IvanovicAuthors Info & Claims

Artificial Intelligence Review, Volume 33, Issue 3

Pages 187 - 209

https://doi.org/10.1007/s10462-009-9153-2

Published: 01 March 2010 Publication History

Abstract

Social tagging systems have grown in popularity over the Web in the last years on account of their simplicity to categorize and retrieve content using open-ended tags. The increasing number of users providing information about themselves through social tagging activities caused the emergence of tag-based profiling approaches, which assume that users expose their preferences for certain contents through tag assignments. Thus, the tagging information can be used to make recommendations. This paper presents an overview of the field of social tagging systems which can be used for extending the capabilities of recommender systems. Various limitations of the current generation of social tagging systems and possible extensions that can provide better recommendation capabilities are also considered.

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cover image Artificial Intelligence Review

Artificial Intelligence Review Volume 33, Issue 3

March 2010

98 pages

ISSN:0269-2821

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Copyright © Copyright © 2010 Springer Science+Business Media B.V.

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Kluwer Academic Publishers

United States

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Published: 01 March 2010

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Kvifte TElahi MTrattner C(2021)Hybrid Recommendation of Movies Based on Deep Content FeaturesService-Oriented Computing – ICSOC 2021 Workshops10.1007/978-3-031-14135-5_3(32-45)Online publication date: 22-Nov-2021
https://dl.acm.org/doi/10.1007/978-3-031-14135-5_3
Shokeen JRana C(2020)A study on features of social recommender systemsArtificial Intelligence Review10.1007/s10462-019-09684-w53:2(965-988)Online publication date: 1-Feb-2020
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Valderas PTorres VPelechano V(2020)A social network for supporting end users in the composition of services: definition and proof of conceptComputing10.1007/s00607-020-00796-8102:8(1909-1940)Online publication date: 1-Aug-2020
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