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An Intelligent On-line Recommendation System in B2C Apparel e-Commerce

Current apparel e-commerce systems support online shopping based on electronic product catalogs. The major issues associated with catalog-based commerce systems are: difficulty in distinguishing one retailer from another, complex navigation with confusing links, and a lack of personalized service. This paper reports an intelligent solution to address these issues. Our solution will provide a personalized apparel recommendation B2C application system through the use of an apparel design knowledge model that includes both the apparel dressing rules as well as the corresponding customer personal information used for reasoning. Based on this solution, we proposed an intelligent apparel on-line recommendation platform that is supported by a framework which provides the desired personalization. This paper reports our design and analysis for this system.