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http://dx.doi.org/10.9709/JKSS.2010.19.4.059

A Personalized Clothing Recommender System Based on the Algorithm for Mining Association Rules  

Lee, Chong-Hyeon (고려대학교 컴퓨터.전파통신공학과)
Lee, Suk-Hoon (고려대학교 컴퓨터.전파통신공학과)
Kim, Jang-Won (고려대학교 컴퓨터.전파통신공학과)
Baik, Doo-Kwon (고려대학교 컴퓨터.전파통신공학과)
Publication Information
Journal of the Korea Society for Simulation / v.19, no.4, 2010 , pp. 59-66 More about this Journal
Abstract
We present a personalized clothing recommender system - one that mines association rules from transaction described in ontologies and infers a recommendation from the rules. The recommender system can forecast frequently changing trends of clothing using the Onto-Apriori algorithm, and it makes appropriate recommendations for each users possible through the inference marked as meta nodes. We simulates the rule generator and the inferential search engine of the system with focus on accuracy and efficiency, and our results validate the system.
Keywords
Personalized Recommender; Ontology Inference; Mining Association Rules;
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Times Cited By KSCI : 1  (Citation Analysis)
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