User Reviews based Product Feature Mining of Mobile Phones in E-commerce
With the popularity of e-commerce and the application about Web 2.0, consumers actively comment on the product they are interested in.Product review mining aims to quickly extract useful information from massive comments published by users and adopt an intuitive way to help consumers make purchasing decisions.Fine-grained product feature mining is very important, however, the product characteristics semantics (upper and lower characteristics、 synonymous features) analysis is inadequate on existing product reviews researches.First the ontology of mobile phone features is constructed based on mobile phone descriptions.Then crawling programs is employed to get product comments and followed by conducting words segmentation, part of speech tagging, getting rid of the repeats and other pretreatments.The Apriori algorithm is designed to extract the appropriate product features from users perspective, and then combined with HowNet dictionary semantic extension is carried to improve the ontology of product features, which will facilitate further accurate sentiment analysis of the product reviews.
product review mining semantic ontology e-commerce HowNet
GAO Hui-yinga NIAN Fu-xing
School of Management and Economics,Beijing Institute of Technology,Beijing 100081,China
国际会议
2013 International Conference on Business Analytics and Management Science (2013商务分析与管理科学国际会议)
北京
英文
31-44
2013-11-23（万方平台首次上网日期，不代表论文的发表时间）