一种基于特征加权语言模型的微博分类新方法

微博作为社交媒体的后起之秀,已经得到快速的发展。微博快速的发展在带给人们便利的同时,也使人们置身于信息的海洋。针对微博中日益呈现出的信息过载问题,微博分类已经成为一个重要的研究课题。针对微博分类,提出一种基于特征加权语言模型的微博分类新方法。 在新浪微博上抽取的真实标注数据集上进行的对比实验结果表明,所提方法是一个有效的微博分类方法。

New Method of Microblog Classification Based on Feature Weighted Language Model

Microblog as a new social media has been rapid development.Microblog rapid development brings convenience to people at the same time,also makes people swimming in the ocean of information.Aiming at the increase in microblog presented the problem of information overload,microblog retrieval has become an important research topic.For microblog retrieval,this paper proposed a new microblog retrieval method based on feature weighted language model,and this method is mainly used in microblog statistical characteristics and semantic characteristics of combined to solve the retrieval problem of the microblog.Experiments were performed on the real annotation data set extracted from sina microblog,and the comparative experimental results show that the proposed method is an effective retrieval method.