Clustering verb, adjective, adjectival-verb concepts using proximity relation

Author

Fujimoto, Taro ; Sugeno, Michio

Author_Institution

Dept. of Syst. Sci., Tokyo Inst. of Technol., Japan

Volume

1

fYear

1997

fDate

1-5 Jul 1997

Firstpage

231

Abstract

This paper deals with clustering verb, adjective, epithet-verb concepts, using fuzzy proximity relation, in the view point of noun connection which is called the Theme-Rheme structure. Similarity relation S is denoted between two verbs which own same nouns. That is why similar verbs connect same nouns. After denoting S to all verbs, α-cut the S and make similar groups among the verbs, adjectives and epithet-verbs. The groups and singular verbs consist of verb classes. In a similar way, S is denoted between two adjectives and between two epithet-verbs, and makes adjective classes and epithet-verb classes. 131 to 194 verb classes, 5 to 34 adjective classes and 39 epithet-verb classes are acquired. This research is based on the construction of the situation database and Japanese ideational semantic network in systemic functional grammar

Keywords

fuzzy set theory; grammars; natural languages; pattern classification; semantic networks; Japanese ideational semantic network; Theme-Rheme structure; adjective; clustering; epithet-verb; fuzzy proximity relation; knowledge discovery; linguistic systems; natural language; noun connection; situation database; systemic functional grammar; verbs; Data mining; Databases; Dictionaries; Equations; Fuzzy systems; Natural language processing; Natural languages; Uncertainty; User interfaces; World Wide Web;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International Conference on

Conference_Location

Barcelona

Print_ISBN

0-7803-3796-4

Type

conf

DOI

10.1109/FUZZY.1997.616373

Filename

616373