Abstract: In the face of massive, heterogeneous, dynamic text information, automatic text classification is of great significance. In recent years, the swarm intelligence theory and method, which has been gradually developed, provides a new intelligent method for text categorization. This paper attempted to introduce the mature particle swarm intelligence algorithm to the text classification field. The text preprocessing model was constructed, which was the foundation of text categorization model. A text categorization model Text PSO-Miner based on PSO was constructed and tested and compared on the vector space matrix of text set. Text PSO-Miner performance indicators were better than the classic classification model（SVM,KNN,NB） and ACO based text classification model. The results showed that Text PSO-Miner can be better applied to text categorization.

Key words: swarm intelligence