Proceedings of the 2016 2nd International Conference on Materials Engineering and Information Technology Applications (MEITA 2016)

Decryption of Full Text Retrieval Technology: Chinese Word Segmentation

Authors
Xuebing Lu, Yili Xu, Weiwei Deng, Yingjie Yan
Corresponding Author
Xuebing Lu
Available Online February 2017.
DOI
10.2991/meita-16.2017.69How to use a DOI?
Keywords
Segmentation Method, Recognition, Chinese Word Segmentation
Abstract

Based on the development of full text retrieval function of administrative office system of Shanghai Entry-Exit Inspection and Quarantine Bureau, this paper comprehensive introduces the Chinese segmentation technology used in full-text retrieval. The three mentioned methods, which are segmentation method based on string matching, the segmentation method based on comprehension and the segmentation method based on statistics. The advantages and disadvantages of the three segmentation methods are compared in this paper. The two difficult points of ambiguity recognition and new word recognition are also discussed in the paper.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 2nd International Conference on Materials Engineering and Information Technology Applications (MEITA 2016)
Series
Advances in Engineering Research
Publication Date
February 2017
ISBN
978-94-6252-304-3
ISSN
2352-5401
DOI
10.2991/meita-16.2017.69How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xuebing Lu
AU  - Yili Xu
AU  - Weiwei Deng
AU  - Yingjie Yan
PY  - 2017/02
DA  - 2017/02
TI  - Decryption of Full Text Retrieval Technology: Chinese Word Segmentation
BT  - Proceedings of the 2016 2nd International Conference on Materials Engineering and Information Technology Applications (MEITA 2016)
PB  - Atlantis Press
SP  - 334
EP  - 337
SN  - 2352-5401
UR  - https://doi.org/10.2991/meita-16.2017.69
DO  - 10.2991/meita-16.2017.69
ID  - Lu2017/02
ER  -