A method of extracting related words using standardized mutual information

被引：0

作者：

Sugimachi, T ^{[1
]}

Ishino, A ^{[1
]}

Takeda, M ^{[1
]}

Matsuo, F ^{[1
]}

机构：

[1] Kyushu Univ, Dept Informat, Higashi Ku, Fukuoka 8128581, Japan

来源：

DISCOVERY SCIENCE, PROCEEDINGS | 2003年 / 2843卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Techniques of automatic extraction of related words are of great importance in many applications such as query expansion and automatic thesaurus construction. In this paper, a method of extracting related words is proposed basing on the statistical information about the co-occurrences of words from huge corpora. The mutual information is one of such statistical measures and has been used for application mainly in natural language processing. A drawback is, however, the mutual information depends mainly on frequencies of words. To overcome this difficulty, we propose as a new measure a normalize deviation of mutual information. We also reveal a correspondence between word ambiguity and related words using word relation graphs constructed using this measure.

引用

页码：478 / 485

页数：8

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