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  5. Unsupervised Statistical Segmentation of Japanese Kanji Strings

Unsupervised Statistical Segmentation of Japanese Kanji Strings

File(s)
99-1756.pdf (139.98 KB)
99-1756.ps (329.79 KB)
Permanent Link(s)
https://hdl.handle.net/1813/7410
Collections
Computer Science Technical Reports
Author
Ando, Rie
Lee, Lillian
Abstract

Word segmentation is an important issue in Japanese language processing because Japanese is written without space delimiters between words. We propose a simple dictionary-less method to segment Japanese kanji sequences into words based solely on character $n$-gram counts from an unannotated corpus. The performance was often better than that of rule-based morphological analyzers over a variety of both standard and novel error metrics.

Date Issued
1999-07
Publisher
Cornell University
Keywords
computer science
•
technical report
Previously Published as
http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR99-1756
Type
technical report

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