面向微博内容的信息抽取模型研究  

Research on Information Extration Model for Microblog Content

作　　者：郑影[1] 李大辉[1] 

机构地区：[1]齐齐哈尔大学计算机与控制工程学院,齐齐哈尔161006

出　　处：《计算机科学》2014年第2期270-275,共6页Computer Science

基　　金：齐齐哈尔大学青年教师科研启动支持计划项目(2011k-M03);黑龙江省自然科学基金项目(F201218)资助

摘　　要：社会媒体是人们用来分享意见、见解、观念和经验的平台或工具,目前已经发展成具有重大影响力的新媒体。而微博作为社会媒体的一个重要部分,对信息的传播起到了很大的作用。面向微博内容的信息抽取就是要从充满噪音的、零碎的、非结构化的微博内容的自由文本中提取有价值的结构化的信息,以利于从微博内容中有效地获取信息。提出了一种基于因子图的微博事件抽取方法来准确地抽取微博中所反映的事件。最后通过实验验证了该方法在性能和准确性上都比其他的方法要高。Social media is the platform or tool that people use to share opinions, insights, ideas and experience. It has be- come the new media having great influence. Microblogging is an important part of social media, so it will play an impor- tant role in the information transfer. Microblogged content-oriented information extraction is to extract the valuable structred information from free text of full of noise, loose, unstructured microblogging content to facilitate effective ac- cess to information from Twitter content. This paper proposed a microblogging event extraction based on factor graph approach to accurately extract the events reflected in microblogging. At last we used some experiments to verify the ef- fectiveness of the methods, and the results show that the performance and accuracy of this method is higher than other methods.

关 键 词：社会媒体 微博 事件抽取 因子图 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]