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
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