Title :
Document categorization algorithm based on kernel NPE
Author :
Wang, Ziqiang ; Sun, Xia ; Zhang, Qingzhou
Author_Institution :
Sch. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou, China
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.
Keywords :
document handling; support vector machines; SVM; document categorization algorithm; document classification problem; kernel NPE; kernel neighborhood preserving embedding; Classification algorithms; Data mining; Databases; Information retrieval; Kernel; Large scale integration; Pattern recognition; Space technology; Support vector machine classification; Support vector machines; Data mining; Document classification; Kernel method; Neighborhood preserving embedding;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
DOI :
10.1109/CCDC.2009.5191820
