Application of Vague Set in Recommender Systems

Cui Chunsheng (), Zang Zhenchun (), Liu Feng () and Qu Ying
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Cui Chunsheng: Henan University of Economics and Law
Zang Zhenchun: Henan University of Economics and Law
Liu Feng: Central Institute for Correctional Police
Qu Ying: HeiBei University of Science and Technology

A chapter in LISS 2012, 2013, pp 1353-1359 from Springer

Abstract: Abstract In the paper, vague set theory is introduced into the study of recommender systems to solve its core problem which is similarity. The existence of uncertainty of customer behavior in the course of e-commerce provides a theoretical basis for the introduction of Vague set. Recommendation of goods relies on the degree of similarity between customers or goods, while the calculation of similarity is a mature area in the research of Vague set. First, Different customer types are identified according to the general shopping way in e-commerce. Then based on the customer classification, statistical methods are used to define the Vague value of the commodity. This method makes a perfect combination e-commerce recommendation system and Vague set and provides new idea for the study of e-commerce recommendation system.

Keywords: Recommender systems; Similarity; Vague set; Vague value (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-32054-5_192

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DOI: 10.1007/978-3-642-32054-5_192

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