DocumentCode
2780972
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
fYear
2009
fDate
17-19 June 2009
Firstpage
2958
Lastpage
2961
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/CCDC.2009.5191820
Filename
5191820
Link To Document