DocumentCode :
2260175
Title :
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
Link To Document :
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