Chinese Text Classification Based On LDA and KSVM
- https://doi.org/10.2991/jimet-15.2015.70How to use a DOI?
- Machine Learning,Text Classification, LDA, KSVM, KNN, SVM-KNN
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.
- © 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/).
Cite this article
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 - https://doi.org/10.2991/jimet-15.2015.70 ID - Liang2015/12 ER -