Summary
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SVM and Collaborative Filtering-Based Prediction of User Preference for Digital Fashion Recommendation Systems Hanhoon KANG Seong Joon YOO Publication IEICE TRANSACTIONS on Information and Systems Vol.E90-D No.12 pp.2100-2103 Publication Date: 2007/12/01 Online ISSN: 1745-1361 DOI: 10.1093/ietisy/e90-d.12.2100 Print ISSN: 0916-8532 Type of Manuscript: LETTER Category: Data Mining Keyword: personalized search, recommendation, machine learning, Full Text: PDF(306.7KB)>>
Summary: In this paper, we describe a method of applying Collaborative Filtering with a Machine Learning technique to predict users' preferences for clothes on online shopping malls when user history is insufficient. In particular, we experiment with methods of predicting missing values, such as mean value, SVD, and support vector regression, to find the best method and to develop and utilize a unique feature vector model. | ||||||||||
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