International Journal of Computational Intelligence Systems

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Volume 10, Issue 1, 2017, Pages 776 - 803

Fuzzy Tools in Recommender Systems: A Survey

Authors
Raciel Yera1, yeratoledo@gmail.com, Luis Martínez2, martin@ujaen.es
1University of Ciego deÁvila, Carretera a Morón Km. 9 1/2, Ciego deÁvila, Cuba
2Computer Science Department, University of Jaén, Campus Las Lagunillas, 23071, Jaén, Spain
Received 18 November 2016, Accepted 25 February 2017, Available Online 13 March 2017.
DOI
10.2991/ijcis.2017.10.1.52How to use a DOI?
Keywords
recommender systems; user preferences; fuzzy logic; survey
Abstract

Recommender systems are currently successful solutions for facilitating access for online users to the information that fits their preferences and needs in overloaded search spaces. In the last years several methodologies have been developed to improve their performance. This paper is focused on developing a review on the use of fuzzy tools in recommender systems, for detecting the more common research topics and also the research gaps, in order to suggest future research lines for boosting the current developments in fuzzy-based recommender systems. Specifically, it is developed an analysis of the papers focused at such aim, indexed in Thomson Reuters Web of Science database, in terms of they key features, evaluation strategies, datasets employed, and application areas.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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<Previous Article In Issue
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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
10 - 1
Pages
776 - 803
Publication Date
2017/03/13
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.2017.10.1.52How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Raciel Yera
AU  - Luis Martínez
PY  - 2017
DA  - 2017/03/13
TI  - Fuzzy Tools in Recommender Systems: A Survey
JO  - International Journal of Computational Intelligence Systems
SP  - 776
EP  - 803
VL  - 10
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2017.10.1.52
DO  - 10.2991/ijcis.2017.10.1.52
ID  - Yera2017
ER  -