DocumentCode
3230545
Title
A PSO-Based Web Document Classification Algorithm
Author
Wang, Ziqiang ; Zhang, Qingzhou ; Zhang, Dexian
Author_Institution
Henan Univ. of Technol., Zhengzhou
Volume
3
fYear
2007
fDate
July 30 2007-Aug. 1 2007
Firstpage
659
Lastpage
664
Abstract
Due to the exponential growth of documents in the Internet and the emergent need to organize them, the automatic document classification has received an ever-increased attention in the recent years. The particle swarm optimization (PSO) algorithm, new to the document classification community, is a robust stochastic evolutionary algorithm based on the movement and intelligence of swarms. In this paper, a PSO-based algorithm for document classification is presented. Comparison between our method and other conventional document classification algorithms is conducted on Reuter and TREC corpora. The experimental results indicate that our proposed algorithm yields much better performance than other conventional algorithms.
Keywords
Internet; classification; document handling; evolutionary computation; particle swarm optimisation; Internet; PSO-based Web document classification algorithm; automatic document classification; particle swarm optimization; robust stochastic evolutionary algorithm; Artificial intelligence; Classification algorithms; Classification tree analysis; Databases; Evolutionary computation; Genetic algorithms; Internet; Neural networks; Particle swarm optimization; Software engineering;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference on
Conference_Location
Qingdao
Print_ISBN
978-0-7695-2909-7
Type
conf
DOI
10.1109/SNPD.2007.72
Filename
4287933
Link To Document