Hybrid approach for Khmer unknown word POS guessing

被引：0

作者：

Nou, Chenda ^{[1
]}

Kameyama, Wataru ^{[1
]}

机构：

[1] Waseda Univ, Grad Sch Global Informat & Telecommun Studies, 1011 Nishi Tomida, Honjo, Saitama 3670035, Japan

来源：

IRI 2007: PROCEEDINGS OF THE 2007 IEEE INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION | 2007年

关键词：

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

New words are being created everyday and the lexicon is not large enough to cover all the words, unknown words become a serious problem in part-of-speech tagging. This paper presents a hybrid approach to handle the unknown word problem in Khmer part-of-speech tagging. The hybrid approach combined of rule-based model and trigram model makes use of both internal structure of the word and surrounding contextual information to predict the part-of-speech of unknown words. The proposed approach achieves 88.9% and 78.2% of accuracy on training and test data respectively.

引用

页码：215 / +

页数：2

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