DocumentCode
458864
Title
Combining Multi-knowledge for Chinese Word Segmentation Disambiguation
Author
Qin Ying ; Zhang Suxiang ; Wang Xiaojie
Author_Institution
Sch. of Inf. Eng., Beijing Univ. of Posts & Telecommun.
Volume
1
fYear
2006
fDate
16-18 Oct. 2006
Firstpage
551
Lastpage
556
Abstract
In the task of Chinese word segmentation, there are two main segmentation ambiguities, overlapping ambiguity and combination ambiguity. The paper analyzes properties of ambiguities and supposes multi-knowledge approach to disambiguate. Multi-knowledge refers to the knowledge from statistic of large corpus and syntactic, semantic or discourse information about ambiguous words. Class based N-gram and maximum entropy model are applied to combining multi-knowledge and disambiguation
Keywords
maximum entropy methods; natural language processing; Chinese word segmentation; N-gram; ambiguous words; combination ambiguity; disambiguation; discourse information; large corpus statistic; maximum entropy model; multiknowledge; overlapping ambiguity; semantic information; syntacticinformation; Concrete; Entropy; Grounding; Humans; Information processing; Intelligent systems; Natural languages; Power engineering and energy; Statistics; Vocabulary;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
Conference_Location
Jinan
Print_ISBN
0-7695-2528-8
Type
conf
DOI
10.1109/ISDA.2006.124
Filename
4021498
Link To Document