Construction of a Probabilistic hierarchical structure based on a Japanese corpus and a Japanese thesaurus

被引:0
|
作者
Terai, Asuka [1 ]
Liu, Bin [2 ]
Nakagawa, Masanori [1 ]
机构
[1] Tokyo Inst Technol, Meguro Ku, 2-12-1 Ookayama, Tokyo 152, Japan
[2] Nissay Informat Technol Co Ltd, Tokyo, Japan
基金
日本学术振兴会;
关键词
D O I
10.1007/978-3-540-78159-2_13
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The purpose of this study is to construct a probabilistic hierarchical structure of categories based on a statistical analysis of Japanese corpus data and to verify the validity of the structure by conducting a psychological experiment. At first, the co-occurrence frequencies of adjectives and nouns within modification relations were extracted from a Japanese corpus. Secondly, a probabilistic hierarchical structure was constructed based on the probability, P (category I noun), representing the category membership of the nouns, and utilizing categorization information in a thesaurus and a soft clustering method (Rose's method [1]) with co-occurrence frequencies as initial values. This method makes it possible to identify the constructed hierarchical structure. In order to examine the validity of the constructed hierarchy, a psychological experiment was conducted. The results of the experiment verified the psychological validity of the hierarchical structure.
引用
收藏
页码:132 / +
页数:3
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