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Unsupervised Word Sense Disambiguation and Rules Extraction using non-aligned bilingual corpus
Oliveera F.1; Wong F.1; Li Y.1; Zheng J.2
2005-12-01
Conference NameInternational Conference on Natural Language Processing and Knowledge Engineering
Source PublicationProceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE'05
Volume2005
Pages30-35
Conference DateOCT 30-NOV 01, 2005
Conference PlaceWuhan, PEOPLES R CHINA
Abstract

This paper presents a statistical Word Sense Disambiguation with application in Portuguese-Chinese Machine Translation systems. Due to the limited availability of Portuguese-Chinese resources in the form of digital corpora and annotated Treebank, an unsupervised learning and a non-aligned bilingual corpus are applied. The proposed method first identifies words related to each of the ambiguous words based on their surrounding words and relative distance. A mathematical model is then applied in the identification of the most suitable sense of an ambiguous word in terms of the related words. All the senses discovered are converted into a set of rules and stored in the Sense Knowledge base for later use in disambiguation and translation process. Preliminary experiment results show an improvement of 6% in assigning correctly the corresponding translation over the baseline method. © 2005 IEEE.

KeywordMachine Translation Natural Language Processing Word Sense Disambiguation
DOI10.1109/NLPKE.2005.1598702
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Information Systems
WOS IDWOS:000235577200007
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Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Universidade de Macau
2.Tsinghua University
Recommended Citation
GB/T 7714
Oliveera F.,Wong F.,Li Y.,et al. Unsupervised Word Sense Disambiguation and Rules Extraction using non-aligned bilingual corpus[C],2005:30-35.
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