Chinese Text Classification Based on Particle Swarm Optimization

DOI

10.2991/nceece-15.2016.11How to use a DOI?

Keywords

Text processing; Classification; Artificial Intelligence; Particle swarm optimization (PSO)

Abstract

For mass, heterogeneous and dynamic text information, it has important significance to the text classification. In recent years, the theory and method of Swarm Intelligence has been developed gradually, which provides a new method for text classification. In this paper, the intelligent algorithm of swarm intelligence, Particle Swarm Optimization (PSO), is introduced into the field of text classification. A text classification model Text PSO-Miner based on PSO is constructed and tested on the Chinese text set. The results show that Text PSO-Miner can be well applied to Chinese text classification.

Copyright

© 2016, 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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TY  - CONF
AU  - Xin Luo
PY  - 2015/12
DA  - 2015/12
TI  - Chinese Text Classification Based on Particle Swarm Optimization
BT  - Proceedings of the 2015 4th National Conference on Electrical, Electronics and Computer Engineering
PB  - Atlantis Press
SP  - 53
EP  - 58
SN  - 2352-5401
UR  - https://doi.org/10.2991/nceece-15.2016.11
DO  - 10.2991/nceece-15.2016.11
ID  - Luo2015/12
ER  -