计算机工程与应用2013，Vol.49Issue(2)：188-193,6.DOI:10.3778/j.issn.1002-8331.1210-0169
使用多元语义特征的评论文本主题聚类
Exploiting multiple semantic features for comment text topic clustering
摘要
Abstract
The feature is a key to the tasks of emotional analysis and opinion mining. Particularly for unsupervised text clustering task, the text feature quality directly affects the clustering results. This paper studies three kinds of semantic features, namely nouns features, noun phrase features, semantic role features and their role on the text topic clustering. And considering the compatibility between the different features, a method is proposed to eliminate redundant features. The method can effectively remove redundant features to improve the clustering accuracy. Also another method is proposed based on semantic role labeling to directly and effectively locate word features for topic clustering. The experimental results indicate that the method is direct and effective, and a new approach to feature selection method is provided.关键词
文本主题聚类/名词特征/短语特征/语义角色特征/相容关系Key words
text topic clustering/ nouns features/ nouns phrase features/ semantic role features/ compatibility relation分类
信息技术与安全科学引用本文复制引用
李亚红,王素格,李德玉..使用多元语义特征的评论文本主题聚类[J].计算机工程与应用,2013,49(2):188-193,6.基金项目
国家自然科学基金(No.61175067,No.60970014,No.61272095) （No.61175067,No.60970014,No.61272095）
山西省自然科学基金(No.2010011021-1) （No.2010011021-1）
山西省科技攻关项目(No.20110321027-02). （No.20110321027-02）
