A method of building Chinese field association knowledge from Wikipedia

Author

Wang, Li ; Yata, Susumu ; Atlam, El-Sayed ; Fuketa, Masao ; Morita, Kazuhiro ; Bando, Hiroaki ; Aoe, Jun-Ichi

Author_Institution

Dept. of Inf. Sci. & Intell. Syst., Univ. of Tokushima, Tokushima, Japan

fYear

2009

fDate

24-27 Sept. 2009

Firstpage

1

Lastpage

5

Abstract

Field association (FA) terms form a limited set of discriminating terms that give us the knowledge to identify document fields. The primary goal of this research is to make a system that can imitate the process whereby humans recognize the fields by looking at a few Chinese FA terms in a document. This paper proposes a new approach to build a Chinese FA terms dictionary automatically from Wikipedia. 104,532 FA terms are added in the dictionary. The resulting FA terms by using this dictionary are applied to recognize the fields of 5,841 documents. The average accuracy in the experiment is 92.04%. The results show that the presented method is effective in building FA terms from Wikipedia automatically.

Keywords

Web sites; dictionaries; document handling; feature extraction; natural language processing; Chinese FA term dictionary; Wikipedia; automatic Chinese field association term knowledge building; document field term identification; feature extraction; Dictionaries; Humans; Information science; Intelligent structures; Intelligent systems; Internet; Knowledge engineering; Rockets; Systems engineering and theory; Wikipedia; Chinese documents; Feature fields; Field association terms; Field recognition; Wikipedia;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Language Processing and Knowledge Engineering, 2009. NLP-KE 2009. International Conference on

Conference_Location

Dalian

Print_ISBN

978-1-4244-4538-7

Electronic_ISBN

978-1-4244-4540-0

Type

conf

DOI

10.1109/NLPKE.2009.5313781

Filename

5313781