DocumentCode
3462015
Title
Error analysis of Chinese text segmentation using statistical approach
Author
Yang, Christopher C. ; Li, K.W.
Author_Institution
Dept. of Syst. Eng. & Eng. Manage., Chinese Univ. of Hong Kong, Shatin, China
fYear
2004
fDate
7-11 June 2004
Firstpage
256
Lastpage
257
Abstract
The Chinese text segmentation is important for the indexing of Chinese documents, which has significant impact on the performance of Chinese information retrieval. The statistical approach overcomes the limitations of the dictionary based approach. The statistical approach is developed by utilizing the statistical information about the association of adjacent characters in Chinese text collected from the Chinese corpus. Both known words and unknown words can be segmented by the statistical approach. However, errors may occur due to the limitation of the corpus. In this work, we have conducted the error analysis of two Chinese text segmentation techniques using statistical approach, namely, boundary detection and heuristic method. Such error analysis is useful for the future development of the automatic text segmentation of Chinese text or other text in oriental languages. It is also helpful to understand the impact of these errors on the information retrieval system in digital libraries.
Keywords
computational linguistics; error analysis; indexing; information retrieval; natural languages; statistical analysis; text analysis; Chinese document indexing; Chinese information retrieval; Chinese text segmentation; boundary detection; digital libraries; error analysis; heuristic method; information retrieval system; statistical approach; Content based retrieval; Dictionaries; Error analysis; Indexing; Information retrieval; Mutual information; Natural languages; Research and development management; Software libraries; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Libraries, 2004. Proceedings of the 2004 Joint ACM/IEEE Conference on
Print_ISBN
1-58113-832-6
Type
conf
DOI
10.1109/JCDL.2004.1336133
Filename
1336133
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