DocumentCode :
1930802
Title :
Automatic extraction of Arabic multi-word terms
Author :
Al Khatib, K. ; Badarneh, Amer
Author_Institution :
Dept. of Comput. Sci., Jordan Univ. of Sci. & Technol., Irbid, Jordan
fYear :
2010
fDate :
18-20 Oct. 2010
Firstpage :
411
Lastpage :
418
Abstract :
Whereas a wide range of methods has been conducted to English multi-word terms (MWTs) extraction, relatively few studied have been applied to Arabic MWTs extraction. In this paper, we present an efficient approach for automatic extraction of Arabic MWTs. The approach relies on two main filtering steps: the linguistic filter, where simple part of speech (POS) tagger is used to extract candidate MWTs matching given syntactic patterns, and the statistical filter, where two statistical methods (log-likelihood ratio and C-value) are used to rank candidate MWTs. Many types of variations (e.g. inflectional variants) are taken into consideration to improve the quality of extracted MWTs. We obtained promising results in both coverage and precision of MWTs extraction in our experiments based on environment domain corpus.
Keywords :
feature extraction; information filtering; natural language processing; statistical analysis; MWT; POS; arabic multiword terms; automatic extraction; linguistic filter; log likelihood ratio; multiword terms; part of speech; statistical filter; syntactic patterns; Barium; Computer science; Information technology; Iron; Syntactics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Technology (IMCSIT), Proceedings of the 2010 International Multiconference on
Conference_Location :
Wisla
ISSN :
2157-5525
Print_ISBN :
978-1-4244-6432-6
Type :
conf
DOI :
10.1109/IMCSIT.2010.5679929
Filename :
5679929
Link To Document :
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