A New Method of Text Feature Selection for Knowledge Discovery
- DOI
- 10.2991/isrme-15.2015.363How to use a DOI?
- Keywords
- knowledge discovery; data mining; information model
- Abstract
In the paper, we considered the problem to model the text document for knowledge discovery. It is urgent problem to find valuable information knowledge in the mass text documents. Data mining based on eigenvector is widely used to mine association between information of mass documents as much as possible for knowledge discovery. However, traditional information model methods for text are hard to achieve the feature vector for some special knowledge discovery task. This paper proposed a new feature selection method of text for knowledge discovery, which is useful to find the valuable words of the text for the special knowledge discovery. In addition, the dimension of the feature vector has been reduced by proposed method, which is of great help to improve the efficiency of data mining effectively.
- 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/).
Cite this article
TY - CONF AU - Li Zhang AU - Xing Liu AU - Rong An AU - Xin Zhao AU - Kejia Yi PY - 2015/04 DA - 2015/04 TI - A New Method of Text Feature Selection for Knowledge Discovery BT - Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering PB - Atlantis Press SP - 1787 EP - 1790 SN - 1951-6851 UR - https://doi.org/10.2991/isrme-15.2015.363 DO - 10.2991/isrme-15.2015.363 ID - Zhang2015/04 ER -