摘要
在当前网络购物模式下,在线评论成为消费者制定购买决策的重要信息来源。然而,评论信息的快速积累使消费者在信息处理和使用中面临前所未有的挑战,使得文本挖掘技术的研究意义和实践价值越来越突出。基于近年文本挖掘相关文献的梳理和归纳,本文尝试对在线评论信息挖掘的研究方法和应用做系统的、全面的综述,总结出当前对在线评论信息挖掘的研究集中在信息抽取、情感分析和文本分类三个主流研究方法,以及研究结论的商业应用。最后,本文指出了在线评论信息挖掘的未来研究方向。
The online reviews have become the important information source of consumers making purchase decisions in the current online shopping mode. However, the rapid accumulation of reviews is an unprecedented chal- lenge for consumers in the process of information processing and using, which makes the research value and practi- cal value of text mining technology more and more prominent. We try to do systematic and comprehensive review on online review information mining on the basis of related literatures in recent years, summarizing three mainstream research methods of online review information mining： information extraction, sentiment analysis, text categorization and the commercial application of the research conclusions. Finally, we point out the future research direction based on the current online review information mining research.
出处
《信息资源管理学报》
2016年第1期4-11,共8页
Journal of Information Resources Management
基金
国家自然基金项目"金融市场传闻与澄清公告的信息加工机制研究"(71403138)
山东省软科学项目"山东省科技型小微企业的互联网金融模式研究"(2014RKB01324)的资助
关键词
在线评论
文本挖掘
信息抽取
情感分析
文本分类
Online review Text mining Information extraction Sentiment analysis Text categorization
