A Heuristic Feature Selection Approach for Text Categorization by Using Chaos Optimization and Genetic Algorithm
Joint Authors
Chen, Hao
Jiang, Wen
Li, Canbing
Li, Rui
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-02
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Due to the era of Big Data and the rapid growth in textual data, text classification becomes one of the key techniques for handling and organizing the text data.
Feature selection is the most important step in automatic text categorization.
In order to choose a subset of available features by eliminating unnecessary features to the classification task, a novel text categorization algorithm called chaos genetic feature selection optimization is proposed.
The proposed algorithm selects the optimal subsets in both empirical and theoretical work in machine learning and presents a general framework for text categorization.
Experimental results show that the proposed algorithm simplifies the feature selection process effectively and can obtain higher classification accuracy with a smaller feature set.
American Psychological Association (APA)
Chen, Hao& Jiang, Wen& Li, Canbing& Li, Rui. 2013. A Heuristic Feature Selection Approach for Text Categorization by Using Chaos Optimization and Genetic Algorithm. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1009699
Modern Language Association (MLA)
Chen, Hao…[et al.]. A Heuristic Feature Selection Approach for Text Categorization by Using Chaos Optimization and Genetic Algorithm. Mathematical Problems in Engineering No. 2013 (2013), pp.1-6.
https://search.emarefa.net/detail/BIM-1009699
American Medical Association (AMA)
Chen, Hao& Jiang, Wen& Li, Canbing& Li, Rui. A Heuristic Feature Selection Approach for Text Categorization by Using Chaos Optimization and Genetic Algorithm. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1009699
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1009699