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article

Folksonomy-Based Recommender Systems: A State-of-the-Art Review

Authors:

Alejandro CorbelliniAuthors Info & Claims

International Journal of Intelligent Systems, Volume 31, Issue 4

Pages 314 - 346

https://doi.org/10.1002/int.21753

Published: 01 April 2016 Publication History

Abstract

Collaborative tagging systems, also known as folksonomies, have grown in popularity over the Web on account of their simplicity to organize several types of content e.g., Web pages, pictures, and video using open-ended tags. The rapid adoption of these systems has led to an increasing amount of users providing information about themselves and, at the same time, a growing and rich corpus of social knowledge that can be exploited by recommendation technologies. In this context, tripartite relationships between users, resources, and tags contained in folksonomies set new challenges for knowledge discovery approaches to be applied for the purposes of assisting users through recommendation systems. This review aims at providing a comprehensive overview of the literature in the field of folksonomy-based recommender systems. Current recommendation approaches stemming from fields such as user modeling, collaborative filtering, content, and link-analysis are reviewed and discussed to provide a starting point for researchers in the field as well as explore future research lines.

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Cited By

Xu BLin HLin YGuan Y(2020)Integrating social annotations into topic models for personalized document retrievalSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-019-03998-124:3(1707-1716)Online publication date: 1-Feb-2020
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Wang XZhang YYamasaki TAmsaleg LHuet BLarson MGravier GHung HNgo CTsang Ooi W(2019)User-Aware Folk Popularity RankProceedings of the 27th ACM International Conference on Multimedia10.1145/3343031.3350920(1970-1978)Online publication date: 15-Oct-2019
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Gan MSun LJiang R(2019)GLORYInformation Systems Frontiers10.1007/s10796-017-9797-421:4(925-939)Online publication date: 1-Aug-2019
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cover image International Journal of Intelligent Systems

International Journal of Intelligent Systems Volume 31, Issue 4

April 2016

104 pages

ISSN:0884-8173

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John Wiley and Sons Ltd.

United Kingdom

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Published: 01 April 2016

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Cited By

Xu BLin HLin YGuan Y(2020)Integrating social annotations into topic models for personalized document retrievalSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-019-03998-124:3(1707-1716)Online publication date: 1-Feb-2020
https://dl.acm.org/doi/10.1007/s00500-019-03998-1
Wang XZhang YYamasaki TAmsaleg LHuet BLarson MGravier GHung HNgo CTsang Ooi W(2019)User-Aware Folk Popularity RankProceedings of the 27th ACM International Conference on Multimedia10.1145/3343031.3350920(1970-1978)Online publication date: 15-Oct-2019
https://dl.acm.org/doi/10.1145/3343031.3350920
Gan MSun LJiang R(2019)GLORYInformation Systems Frontiers10.1007/s10796-017-9797-421:4(925-939)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1007/s10796-017-9797-4
Liu H(2019)Resource recommendation via user tagging behavior analysisCluster Computing10.1007/s10586-017-1459-222:1(885-894)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1007/s10586-017-1459-2
Qassimi SAbdelwahed E(2019)The role of collaborative tagging and ontologies in emerging semantic of web resourcesComputing10.1007/s00607-019-00704-9101:10(1489-1511)Online publication date: 1-Oct-2019
https://dl.acm.org/doi/10.1007/s00607-019-00704-9
(2018)A tag-based recommender system framework for social bookmarking websitesInternational Journal of Web Based Communities10.5555/3282769.328277514:3(303-322)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.5555/3282769.3282775
Gan MJiang R(2018)FLOWERFuture Generation Computer Systems10.1016/j.future.2017.02.02778:P1(462-473)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1016/j.future.2017.02.027
Singh ANagwani NPandey S(2017)TAGmeProceedings of the 4th Multidisciplinary International Social Networks Conference10.1145/3092090.3092095(1-7)Online publication date: 17-Jul-2017
https://dl.acm.org/doi/10.1145/3092090.3092095

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