DocumentCode :
2664991
Title :
Improving Xtract for Chinese collocation extraction
Author :
Lu, Qin ; Li, Yin ; Xu, Ruifeng
Author_Institution :
Dept. of Comput., Hong Kong Polytech. Univ., China
fYear :
2003
fDate :
26-29 Oct. 2003
Firstpage :
333
Lastpage :
338
Abstract :
We present a system which extracts word-based bigram and n-gram collocation information from a 60MB corpus and then locates bigram pairs using strength and spread as defined in the Xtract system. In order for Xtract to work effectively with Chinese, we have readjusted the parameters. To obtain a higher recall rate, we have modified the algorithm to identify collocations with low-frequency of occurrence, a method which works particularly well in the case of bigrams in which one word is high-frequency and the other low-frequency. In preliminary experiments, our system extracts bigram collocations with a precision of 61%, an 8% improvement over the direct use Smadja´ Xtract on Chinese. Further, we have improved the recall rate by 4.5% while extracting multiword collocations with 92% precision.
Keywords :
computational linguistics; natural languages; statistical analysis; Chinese collocation extraction; Xtract system; bigram collocation; statistical modeling; Application software; Computer worms; Data mining; Frequency; Humans; Mutual information; Statistical analysis; Sun;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Language Processing and Knowledge Engineering, 2003. Proceedings. 2003 International Conference on
Conference_Location :
Beijing, China
Print_ISBN :
0-7803-7902-0
Type :
conf
DOI :
10.1109/NLPKE.2003.1275925
Filename :
1275925
Link To Document :
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