基于商品特征的商品评论信息挖掘方法  

Method of Review Information Mining Based on Characteristics of Commodity Goods

作　　者：周民[1] 李蕊[1] 

机构地区：[1]南阳理工学院软件学院,河南南阳473004

出　　处：《计算机与现代化》2014年第6期98-101,105,共5页Computer and Modernization

摘　　要：人们在购物网站上发表的评论信息,一方面作为消费者对商品的反馈,同时为潜在的消费者提供购物经验。但是,随着商品评论信息的增加,消费者往往会被淹没在评论信息中。本文采用观点挖掘方法,以商品特征为研究对象,挖掘基于商品某一特征的用户评论信息,计算消费者的情感倾向,确定情感分布。旨在通过对此问题的研究,给消费者提供更明确、更细化的商品评价。Product reviews presented on the Web by the customers are used to be as the feedback on products and meanwhile pro- viding shopping experience for potential customers. However, with the increasing of commodity review information, consumers tend to be submerged in these comments. This paper presents an algorithm for product reviews mining base on opinion mining. First, we collect product reviews using crawler. Second, identify the product features which the customers mention in the view. Third, find the opinion sentences. Last, compute the emotional scores of the opinion sentences and output the emotional distribu- tion. The aims of researching on this question are to provide consumers with more clear, more detailed evaluation to goods.

关 键 词：商品评论 观点挖掘 情感计算 分水岭算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]