A Latent Semantic Analysis Based Method of Getting the Category Attribute of Words

被引:3
作者
Jiang, Zongli [1 ]
Lu, Changdong [1 ]
机构
[1] Beijing Univ Technol, Lab Comp Software & Theory, Beijing, Peoples R China
来源
ICECT: 2009 INTERNATIONAL CONFERENCE ON ELECTRONIC COMPUTER TECHNOLOGY, PROCEEDINGS | 2009年
关键词
information retrieval; search engine; latent semantic analysis; text categorization;
D O I
10.1109/ICECT.2009.19
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Current search engines have two problems, losing useful information and including useless information. These two problems are aroused by the keyword matching retrieval model, which is adopted by almost all search engines. We introduce the conception of category attribute of a word. According to the category attribute of a word, the useless results can he removed from the search results and the retrieval efficiency will he improved. A latent semantic analysis based method of getting the category attribute of the word is presented in this paper, which is proved to be effective by experiment. Latent semantic analysis is a method that can discover the underlying semantic relation between words and documents. Singular value decomposition is used in latent semantic analysis to analyze the words and documents and get the semantic relation finally.
引用
收藏
页码:141 / +
页数:3
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