A fuzzy model for managing natural noise in recommender systems

TitleA fuzzy model for managing natural noise in recommender systems
Publication TypeInternational Journal
Year of Publication2016
AuthorsR. Yera, J. Castro and L. Martínez
JournalApplied Soft Computing
Date Published03/2016
ISSN Number1568-4946
KeywordsComputing with Words

Abstract E-commerce customers demand quick and easy access to products in large search spaces according to their needs and preferences. To support and facilitate this process, recommender systems (RS) based on user preferences have recently played a key role. However the elicitation of customers preferences is not always precise either correct, because of external factors such as human errors, uncertainty and vagueness proper of human beings and so on. Such a problem in \{RS\} is known as natural noise and can bias customers recommendations. Despite different proposals have been presented to deal with natural noise in \{RS\} none of them is able to manage properly the inherent uncertainty and vagueness of customers preferences. Hence, this paper is devoted to a new fuzzy method for managing in a flexible and adaptable way such uncertainty of natural noise in order to improve recommendation accuracy. Eventually a case study is performed to show the improvements produced by this fuzzy method regarding previous proposals.

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