Grasping Related Words of Unknown Word for Automatic Extension of Lexical Dictionary

Author

Hwang, Myunggwon ; Baek, Sunkyoung ; Choi, Junho ; Park, Jongan ; Kim, Pankoo

Author_Institution

Intelligent Comput. Lab, Gwangju

fYear

2008

fDate

23-24 Jan. 2008

Firstpage

31

Lastpage

35

Abstract

An aim of this research is to grasp related words of unknown word. Currently, several lexical dictionaries have been developed for semantic retrieval such as WordNet and FrameNet. However, more new words are created in every day because of new trends, new paradigm, new technology, etc. And, it is impossible to contain all of these new words. The existing methods, which grasp the meaning of unknown word, have a limitation that is not exact. To solve this limitation, we have studied the way how to make relations between known words and unknown word. As a result, we found a noble method using co-occurrence, wordnet and Bayesian probability. The method could find what words are related with unknown word and how much weight other words relate with unknown word.

Keywords

Bayes methods; dictionaries; information retrieval; probability; Bayesian probability; FrameNet; WordNet; automatic extension; lexical dictionary; related words; semantic retrieval; unknown word; Bayesian methods; Data mining; Dictionaries; Information retrieval; Learning systems; Probability; Speech;

fLanguage

English

Publisher

ieee

Conference_Titel

Knowledge Discovery and Data Mining, 2008. WKDD 2008. First International Workshop on

Conference_Location

Adelaide, SA

Print_ISBN

978-0-7695-3090-1

Type

conf

DOI

10.1109/WKDD.2008.151

Filename

4470344