Fuzzy Tools in Recommender Systems: A Survey

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 dev...

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Bibliographic Details
Published inInternational journal of computational intelligence systems Vol. 10; no. 1; pp. 776 - 803
Main Authors Yera, Raciel, Martínez, Luis
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.01.2017
Springer Nature B.V
Springer
Subjects
fuzzy logic
Fuzzy systems
Recommender systems
Research Article
survey
user preferences
survey
recommender systems
user preferences
fuzzy logic
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Summary: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.
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ISSN:1875-6891
1875-6883
1875-6883
DOI:10.2991/ijcis.2017.10.1.52