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HCRS: A hybrid clothes recommender system based on user ratings and product features

Nowadays, online clothes-selling business has become popular and extremely attractive because of its convenience and cheap-and-fine price. Good examples of these successful Web sites include Yintai.com, Vancl.com and Shop.vipshop.com which provide thousands of clothes for online shoppers. The challenge for online shoppers lies on how to find a good product from lots of options. In this article, we propose a collaborative clothes recommender for easy shopping. One of the unique features of this system is the ability to recommend clothes in terms of both user ratings and clothing attributes. Experiments in our simulation environment show that the proposed recommender can better satisfy the needs of users.

preprint2014arXivOpen access
Xiaosong HuWen ZhuQing Li
Information RetrievalArtificial Intelligence
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Open access3 authors2 topics
Imported metadata coverageMissing code, dataset, citation and institution fields are tracked without dominating the paper.Details
Citations: 0Reviews: 0Saves: 0Code: not linkedDataset: not linkedInstitutions: 0

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Xiaosong HuWen ZhuQing Li

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