Chinese Text Classification Based On LDA and KSVM

DOI

10.2991/jimet-15.2015.70How to use a DOI?

Keywords

Machine Learning,Text Classification, LDA, KSVM, KNN, SVM-KNN

Abstract

With the rapid development of information technology and social networking, the amount of generated text data has increased enormously. As one of the crucial technologies for information organization and management, text classification has become much more significant in the area of machine learning and natural language processing. According to this paper, we present a text classification system. First, we apply LDA topic model to express the text instead of Boolean model or vector space model. Then, we choose KSVM which combines SVM with KNN as the classification algorithm. Finally, we choose documents with large amount of Chinese news for experiments. Compared with normal language models, these experimental data shows that our system gets higher classification accuracy.

Copyright

© 2015, 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  - Congwei Liang
AU  - Yong Liu
AU  - Haiqing Du
PY  - 2015/12
DA  - 2015/12
TI  - Chinese Text Classification Based On LDA and KSVM
BT  - Proceedings of the 2015 Joint International Mechanical, Electronic and Information Technology Conference
PB  - Atlantis Press
SP  - 379
EP  - 383
SN  - 2352-538X
UR  - https://doi.org/10.2991/jimet-15.2015.70
DO  - 10.2991/jimet-15.2015.70
ID  - Liang2015/12
ER  -