Purpose-Feature Relationship Mining from Online Reviews towards Purpose-Oriented Recommendation

Sopheaktra YONG  Yasuhito ASANO  

IEICE TRANSACTIONS on Information and Systems   Vol.E101-D   No.4   pp.1021-1029
Publication Date: 2018/04/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2017DAP0013
Type of Manuscript: Special Section PAPER (Special Section on Data Engineering and Information Management)
recommendation system,  review analysis,  bootstrapping,  

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To help with decision making, online shoppers tend to go through both a list of a product's features and functionality provided by the vendor, as well as a list of reviews written by other users. Unfortunately, this process is ineffective when the buyer is confronted with large amounts of information, particularly when the buyer has limited experience with and knowledge of the product. In order to avoid this problem, we propose a framework of purpose-oriented recommendation that presents a ranked list of products suitable for a designated user purpose by identifying important product features to fulfill the purpose from online reviews. As technical foundation for realizing the framework, we propose several methods to mine relation between user purposes and product features from the consumer reviews. Using digital camera reviews on Amazon.com, the experimental results show that our proposed method is both effective and stable, with an acceptable rate of precision and recall.