DocumentCode :
2259368
Title :
Applying tree kernel to Chinese syntactic parsing reranking
Author :
Zheng, Xiaodong ; Chen, Liang ; Chang, Baobao
Author_Institution :
Inst. of Comput. Linguistics, Peking Univ., Beijing, China
fYear :
2009
fDate :
24-27 Sept. 2009
Firstpage :
1
Lastpage :
6
Abstract :
Chinese Syntactic Parsing is often divided into two stages, basic model to generate k-best candidate parsing trees and reranking stage to find the best one in these trees, and we focus on the second stage-reranking. Tree kernel has been used in Syntactic parsing in English(Collins 2002) which makes a good improvement in performance. This paper makes tree kernel method practical for Chinese Syntactic Parsing, and improves tree kernel from three points: the first is introducing rules weights rw to distinct different rules, the second is introducing similar rules converging, and the third is introducing a parameter lambda to scale the relative importance of tree fragments with their size and solve the peak problem which is a common kernel. Experiments show that these three adjustments to tree kernel increase reranking performance a lot.
Keywords :
grammars; tree data structures; Chinese syntactic parsing reranking; candidate parsing tree; tree kernel; Computational linguistics; Kernel; Learning systems; Machine learning algorithms; Partial transmit sequences; Training data; Chinese Syntactic Parsing; Reranking; Tracking; Tree Kernel;
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.2009.5313750
Filename :
5313750
Link To Document :
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