Fuzzy Tools in Recommender Systems: A Survey
Type of publication: International Journal
Year of publication: 2017
Authors: Raciel Yera
Director: Luis Martínez
Type: International Journal of Computational Intelligence Systems
Volumen: 10
Pagination: 776-803
ISSN number: 1875-6883
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 ReutersWeb of Science database, in terms of they key features, evaluation strategies, datasets employed, and application areas.
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