Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/10292
Title: Chunk segmentation of Chinese sentences using a Combined Statistical and Rule-based Approach (CSRA)
Authors: Wang, R
Wang, X
Chen, Z
Chi, Z 
Issue Date: 2007
Source: International journal of computer processing of languages, 2007, v. 20, no. 2, p. 197-218
Abstract: Deep parsing of Chinese sentences is a very challenging task due to their complexity such as ambiguous word boundaries and meanings. An alternative mode of Chinese language processing is to perform shallow parsing of Chinese sentences in which chunk segmentation plays an important role. In this paper, we present a chunk segmentation algorithm using a combined statistical and rule-based approach (CSRA). The decision rules for refining chunk segmentation are generated from incorrectly segmented chunks from a statistical model which is built on a training corpus. Experimental results show that the CSRA works well and produces satisfactory chunk segmentation results for subsequent processes such as chunk tagging and chunk collocation extraction.
Keywords: Chinese language processing
Chinese chunk segmentation
Machine translation
Language modeling
Decision rules
Publisher: World Scientific Publishing Co
Journal: International journal of computer processing of languages 
ISSN: 1793-8406
DOI: 10.1142/S0219427907001676
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