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,  

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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.