Research on the Influence of Part of Speech Selection in Chinese Text Clustering

机译：词类选择对中文文本聚类的影响研究

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Based on three classic clustering algorithms, this paper makes a comparative study about the influence on part of speech in Chinese text clustering. According to the experimental result, noun is the most important part of speech in presenting the content of the document. Besides, verb, adjective and adverb contribute to document clustering. Although the noun can get acceptable performance, but only use the noun features cannot get the best result. Compared with other parts of speech combination and single part of speech, the combination of nouns, verbs, adjectives and adverbs can produce better clustering result.

机译：本文基于三种经典的聚类算法，对中文文本聚类对词性的影响进行了比较研究。根据实验结果，名词是表示文档内容时语音中最重要的部分。此外，动词，形容词和副词也有助于文档聚类。尽管名词可以得到可接受的性能，但是仅使用名词功能不能获得最佳结果。与其他词性组合和单个词性相比，名词，动词，形容词和副词的组合可以产生更好的聚类结果。

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来源
《The 7th China-Japan-Korea joint symposium on optimization of structural and mechanical systems》|2012年|1-10|共10页
会议地点 Huangshan(CN)
作者
Pu Han; Gaofei Lu; Si Shen;
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作者单位

School of Information Management, Nanjing University, Hankou Road 22,210093, Nanjing, P R China;

School of Information Management, Nanjing University, Hankou Road 22,210093, Nanjing, P R China;

School of Information Management, Nanjing University, Hankou Road 22, 210093, Nanjing, P R China;

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会议组织
原文格式 PDF
正文语种 eng
中图分类 TP271.2;
关键词
Information retrieval; Text clustering; Part of speech tagging;

机译：信息检索；文本聚类；语音标记;

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Research on the Influence of Part of Speech Selection in Chinese Text Clustering

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