<abstract xmlns="http://www.w3.org/1999/xhtml"><p> Feature selection is the main step in classification systems, a procedure that selects a subset from original features. Feature selection is one of major challenges in text categorization. The high dimensionality of feature space increases the complexity of text categorization process, because it plays a key role in this process. This paper presents a novel feature selection method based on particle swarm optimization to improve the performance of text categorization. Particle swarm optimization inspired by social behavior of fish schooling or bird flocking. The complexity of the proposed method is very low due to application of a simple classifier. The performance of the proposed method is compared with performance of other methods on the Reuters-21578 data set. Experimental results display the superiority of the proposed method.</p></abstract>

Feature selection is the main step in classification systems, a procedure that selects a subset from original features. Feature selection is one of major challenges in text categorization. The high dimensionality of feature space increases the complexity of text categorization process, because it plays a key role in this process. This paper presents a novel feature selection method based on particle swarm optimization to improve the performance of text categorization. Particle swarm optimization inspired by social behavior of fish schooling or bird flocking. The complexity of the proposed method is very low due to application of a simple classifier. The performance of the proposed method is compared with performance of other methods on the Reuters-21578 data set. Experimental results display the superiority of the proposed method.

Feature Selection Using Particle Swarm Optimization in Text Categorization

Department of Computer Engineering and Information Technology, Payame Noor University (PNU)P.O.BOX 193953697, Tehran, IRAN

School of Computer Engineering Iran University of Science and Technology Tehran, IRAN

Journal of Artificial Intelligence and Soft Computing Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Feature Selection Using Particle Swarm Optimization in Text Categorization"}

Feature selection is the main step in classification systems, a procedure that selects a subset from original features. Feature selection is one of major...

Feature Selection Using Particle Swarm Optimization in Text Categorization

Online veröffentlicht: 29. Okt. 2015

Seitenbereich: 231 - 238

DOI: https://doi.org/10.1515/jaiscr-2015-0031

© 2015

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.