An Efficient Web Document Classification Algorithm Based on LPP and SVM

With the explosive growth of World Wide Web, it is of great importance to develop methods for the automatic classifying of large collections of documents. To efficiently tackle this problem, a novel document classification algorithm based on locality pursuit projection (LPP) and SVM is proposed in this paper. The high-dimensional document space are first mapped into lower-dimensional space with LPP, the SVM is then used to classify the documents into semantically different classes. Experimental results show that the proposed algorithm achieves much better performance than other classification algorithms.