Abstract
As the amount of information available on the internet grows so does the need for more effective data analysis methods. This paper utilizes the particle swarm optimization (PSO) algorithm in the field of web content classification, and used part of speech tagging algorithm to reduce the large numbers of attributes associated with web content mining. The proposed algorithm gave a good classification accuracy, which comparable to the accuracy of Ant-miner algorithm and acquire less training time.
