Metadata based recommender systems
Advances in Computing, Communications and Informatics（2014）
摘要
For building a recommendation system the eCommerce portal gathers the user's ratings on various items in order to determine his/her choice regarding its merchandise. The portal also collects metadata for the user when he/she signs up and becomes a part of the system; therefore the portal has access to information such as user's age, gender, occupation, location, etc. Till date almost all prior studies used the metadata for alleviating the cold-start problem; this information was not used for improving the recommendations. For the first time in this work, we propose a simple neighborhood selection technique by giving importance to the metadata groups for improving the recommendations.
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关键词
electronic commerce,information retrieval,meta data,portals,recommender systems,cold-start problem,ecommerce portal,information access,metadata based recommender systems,metadata groups,simple neighborhood selection technique,user age,user gender,user location,user occupation,user ratings
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