Document Categorization Algorithm Based on Kernel NPE

摘要：

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.

关键词： Document classification Kernel method Neighborhood preserving embedding Data mining

作者: Ziqiang Wang Xia Sun Qingzhou Zhang

作者单位: School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001,China

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 2958-2961

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）