Document categorization algorithm based on kernel NPE

Authors:
Ziqiang Wang;Xia Sun;Qingzhou Zhang
Affiliations:
School of Information Science and Engineering, Henan University of Technology, Zhengzhou, China;School of Information Science and Engineering, Henan University of Technology, Zhengzhou, China;School of Information Science and Engineering, Henan University of Technology, Zhengzhou, China
Venue:
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Year:
2009

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Abstract

To efficiently tackle document classification problem, a novel document classification algorithm based on kernel neighborhood preserving embedding (KNPE) is proposed in this paper. The discriminant features are first extracted by the KNPE algorithm, then SVM is used to classify the documents into semantically different classes. Experimental results on real document databases have demonstrated the better performance of the proposed algorithm.