摘要
企业收集和获取用户个人信息是其对用户行为进行分析以制定合理营销决策的前提。注意到当前,由于互联网的高度发展和普及,消费用户往往在Web上以评论文本的形式分享其消费习惯、消费偏好和消费体验,这些海量的评论文本中蕴含着极具价值的信息,为用户个人信息的收集提供良好的资源。针对传统企业收集用户个人信息的方法主要以人工为主导,自动化水平较低的问题,提出一种基于Web挖掘技术以网上评论文本为挖掘对象,对用户个人信息进行自动提取以自动分析用户行为的改进方法。企业可以通过此改进的用户个人信息提取方法对用户行为进行分析以自动获取消费用户对产品的反馈意见并制定有针对性的营销策略。
It is a premise for an enterprise to make a proper marketing decision based on user behaviour analysis to gather and obtain users＇ personal information.It is noticed that,with the rapid development and population of the Internet,users usually share their consuming habits,preferences and experiences in the form of Web review text comments.There is highly valuable information buried in the vast amount text comments that provides excellent resources for users＇ personal information collection.With respect to the traditional method of gathering users＇ personal information which focuses on manual operation and is poor at automation,an improved method,which is based on Web mining technology that takes online text comments as mining objects to automatically extract users＇ personal information in order to automatically analyse user behaviours,is proposed.Enterprises can acquire customers＇ feedbacks on products automatically by analyzing users＇ behaviours via the improved users＇ personal information extraction method in order to make accurate marketing strategies.
出处
《计算机应用与软件》
CSCD
北大核心
2012年第5期44-47,72,共5页
Computer Applications and Software
基金
国家自然科学基金项目(70971059)
辽宁省创新团队项目(2009T045)
关键词
用户个人信息
用户行为分析
产品特征挖掘
用户特征提取
情感量化
群体识别
Users＇ personal information User behaviour analysis Product feature mining Customer features extraction Emotional quantification Group identification
