Document Classification Algorithm Based on NPE and PSO

With many potential applications in document management and Web searching, document classification has recently gained more attention. To efficiently resolve this problem, an efficient document classification algorithm based on neighborhood preserving embedding (NPE) and particle swarm optimization (PSO) is proposed in this paper. The document features are first extracted by the NPE algorithm, then the PSO classifier is used to classify the documents into semantically different classes. Experimental results show that the proposed algorithm achieves much better performance than other related classification algorithms.