Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015

Chinese Text Classification Based on Ant Colony Optimization

Authors
Xin Luo
Corresponding Author
Xin Luo
Available Online December 2015.
DOI
https://doi.org/10.2991/icmmcce-15.2015.10How to use a DOI?
Keywords
Text processing; classification; Artificial intelligence; Ant colony optimization;
Abstract
It's significance for us to study Chinese Text Classification, when we face so much dynamic information. The development of Text Classification has a close connection with Pattern Recognition. However, some peculiarity of Chinese Text Classification, such as it has many classes, much noise, and excessive samples, make Pattern Recognition difficult to classify texts. Recently, Artificial Intelligence provides a new intellectualized method to Text Classification. This paper tentatively leads Ant Colony Optimization, a ripe algorithm of Swarm Intelligence, into Text Classification. We construct a Text ACO-Miner Classification Model based on Ant Colony Optimization, and test it. The result shows the model can accurately be used to classify Chinese texts.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
2015 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering
Part of series
Advances in Computer Science Research
Publication Date
December 2015
ISBN
978-94-6252-133-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmmcce-15.2015.10How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Xin Luo
PY  - 2015/12
DA  - 2015/12
TI  - Chinese Text Classification Based on Ant Colony Optimization
BT  - 2015 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.10
DO  - https://doi.org/10.2991/icmmcce-15.2015.10
ID  - Luo2015/12
ER  -