文章基本信息

标题：Automatic Generation of Synonyms Using Textual Data
本地全文：下载
作者：Kaname Kasahara ; Nozomu Inago ; Tsuneaki Kato 等
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2003
卷号：18
期号：4
页码：221-232
DOI：10.1527/tjsai.18.221
出版社：The Japanese Society for Artificial Intelligence
摘要：A method of generating synonyms for a stimulus word using a computer is proposed. Vector Space Model, where words in text data are arranged in a multi-dimensional space and degree of similarity between two words of them is calculated from how close the words are in the space, may be available to the method. However, it is not easy to optimize parameters in the method because there is no appropriate standard synonym database where proper synonyms for a stimulus word are thoroughly collected. Therefore, we first built such a standard database employing two steps of human subjects expriments, and optimized the parameters of the method of generating synonyms. As the result, it was found that the Vector Space Model-based method using an electronic dictionary as source is better to generate synonyms than the one using a text corpus and an ordinal method using a thesaurus.
关键词：synonym ; dictionary ; corpus ; similarity ; thesaurus