基于语义理解的文本倾向性识别机制

文本倾向性识别在垃圾邮件过滤、信息安全和自动文摘等领域都有广泛的应用。本文提出了基于语义理解的文本倾向性识别机制。其主要思想是首先计算词汇与知网中已标注褒贬性的词汇间的相似度,获取词汇的倾向性;再选择倾向性明显的词汇作为特征值,用SVM分类器分析文本的褒贬性;最后采用否定规则匹配文本中的语义否定的策略提高分类效果,同时处理程度副词附近的褒义词和贬义词,以加强对文本褒贬义强度的识别。

Text Orientation Identification Based on Semantic Comprehension

At the fields of spam filtering,information security and automatic summarizations,text orientation identification is used widely. The paper presents the mechanism based on Semantic Comprehension for text orientation identification.Firstly,it acquires the semantic orientation through computing semantic similarity the vocabulary and tagged vocabulary in How-Net,and it adopts the derogatory or commendatory terms as features of classification.It utilizes Support Vector Machine classifier to identify the text orientation.Finally it deals with the negative sentence via matching negative rules.At the same time,it also identifies the derogatory or commendatory intensity through degree adverb in order to improve the accuracy of classification.