How to Find Similar Users in Order to Develop a Cosmetics Recommender System
Most shopping web sites allow users to provide product reviews. It has been observed that reviews have a profound effect on item conversion rates. In particular, reviews of cosmetic products have significant impact on purchasing decisions because of the personal nature of such products, and also because of the potential for skin irritation caused by unsuitable items, which is a major consumer concern. In this study, we develop a method for user similarity calculation for a cosmetic review recommender system. To realize such a recommender system, we propose a method for the automatic scoring of various aspects of cosmetic item review texts based on an evaluation expression dictionary curated from a corpus of real-world online reviews. Furthermore, we consider how to calculate user similarity of cosmetic review sites.
KeywordsAutomatic review rating Clustering cosmetic products Evaluation expression dictionary Explanation of reviews Recommender system Text mining User similarity
This work was supported in part by istyle Inc. which provided review data for cosmetic items, and the MEXT Grant-in Aid for Scientific Research(C)(#16K00425, #26330351).
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