Integrate chinese semantic knowledge into word sense disambiguation
Release time:2019-03-11
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期刊论文
First Author:
Chun-Xiang, Zhang
Co-author:
Lu-Rong, Sun,Xue-Yao, Gao,Zhi-Mao, Lu,Yong, Yue
Date of Publication:
2015-01-01
Journal:
International Journal of Hybrid Information Technology
Included Journals:
EI
Document Type:
J
Volume:
8
Issue:
4
Page Number:
105-116
ISSN No.:
17389968
Abstract:
Word sense disambiguation is important for many applications in natural language processing fields including machine translation, information retrieval and automatic summarization. In this paper, left word unit and right word unit are extracted for improving the quality of word sense disambiguation (WSD) starting from the target polysemous word. Their semantic knowledge is mined from Tongyici Cilin which is a Chinese semantic lexicon. A new method of word sense disambiguation is proposed with semantic information of left word unit and right word unit. The classifier of word sense disambiguation is built based on bayesian model. SemEval-2007: Task#5 is used as training corpus and test corpus. Experimental results show that the disambiguation classifier’s precision is improved and demonstrate the effectiveness of the method. © 2015 SERSC
Translation or Not:
no
