...文本情感分类; 向量空间模型; K 均值聚类算法; 支持向量机; 信息增益; 互信息 [gap=1083]Key words: text sentiment classification; vector space model; K-means clustering ; support vector machine; information g..
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The experiment results indicate that the greater text sentiment classification impact depends on other corpus, excluded adjective, verb, adverb as stop words and none stop words.
本文利用三种特征选择方法、两种权重计算方法、五种停用词表以及支持向量机分类器对汽车语料的文本情感类别进行了研究。
This paper introduces a text filtering system merging topic classification based on vector space model and sentiment classification based on support vector machine.
该文介绍了一种文本过滤算法，该算法把基于空间向量模型的主题分类算法与基于支持向量机文本态度分类结合起来。
Text classification of objects related to sentiment words, sentences, paragraphs and chapters.
文本中涉及到情感分类的对象一般有词汇、句子、段落以及篇章。
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