Hits:

Indexed by:期刊论文

Date of Publication:2012-03-01

Journal:CHINA COMMUNICATIONS

Included Journals:SCIE、Scopus

Volume:9

Issue:3

Page Number:58-67

ISSN No.:1673-5447

Key Words:English PoS tagging; maximum entropy; rule-based approach; machine translation; NP chunking

Abstract:A hybrid approach to English Part-of-Speech (PoS) tagging with its target application being English-Chinese machine translation in business domain is presented, demonstrating how a present tagger can be adapted to learn from a small amount of data and handle unknown words for the purpose of machine translation. A small size of 998 k English annotated corpus in business domain is built semiautomatically based on a new tagset; the maximum entropy model is adopted, and rule-based approach is used in post-processing. The tagger is further applied in Noun Phrase (NP) chunking. Experiments show that our tagger achieves an accuracy of 98.14%, which is a quite satisfactory result. In the application to NP chunking, the tagger gives rise to 2.21% increase in F-score, compared with the results using Stanford tagger.