A method of restricted knowledge acquisition from WordNet

Author

Suárez, A. ; Saiz-Noeda, M. ; Palomar, M.

Author_Institution

Dept. Lenguajes y Sistemas Inf., Alicante Univ., Spain

fYear

1999

fDate

36495

Firstpage

38

Lastpage

41

Abstract

The problem with using extensive lexical, syntactic and semantic resources is the large quantity of information that is provided, as well as all the different senses that each word has. To contribute to the resolution of this problem, this paper presents a tool for knowledge acquisition from WordNet, restricting and limiting the learning of word senses. For this purpose, a semantically restricted corpus (Brown Corpus semantic concordance files from the WordNet package) is used, and a restricted “subnet” is obtained, with the word senses related to the text domain

Keywords

data mining; knowledge acquisition; linguistics; natural languages; thesauri; very large databases; Brown Corpus; WordNet; information quantity; lexical resources; restricted knowledge acquisition; semantic concordance files; semantic resources; semantic tagging; semantically restricted corpus; subnet; syntactic resources; text domain; word sense disambiguation; word sense learning; Data mining; Databases; Humans; Information retrieval; Knowledge acquisition; Packaging; Proposals; Psychology; Tagging; Thesauri;

fLanguage

English

Publisher

ieee

Conference_Titel

Knowledge-Based Intelligent Information Engineering Systems, 1999. Third International Conference

Conference_Location

Adelaide, SA

Print_ISBN

0-7803-5578-4

Type

conf

DOI

10.1109/KES.1999.820114

Filename

820114