A PSO-Based Web Document Classification Algorithm

Authors:
Ziqiang Wang;Qingzhou Zhang;Dexian Zhang
Affiliations:
Henan University of Technology, China;Henan University of Technology, China;Henan University of Technology, China
Venue:
SNPD '07 Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03
Year:
2007

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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.