DocumentCode
130983
Title
Research on text classification based on SVM-KNN
Author
Yun Lin ; Jie Wang
Author_Institution
Capital Normal Univ., Beijing, China
fYear
2014
fDate
27-29 June 2014
Firstpage
842
Lastpage
844
Abstract
A new text classification algorithm has been put forward based on basic support vector machine algorithm. The SVM-KNN algorithm for text classification has been proposed which combined SVM algorithm and KNN algorithm. The SVM-KNN algorithm can improve the performance of classifier by the feedback and improvement of classifying prediction probability. The actual effect of SVM-KNN algorithm is tested and the performance is proved in related Chinese web page classification test system.
Keywords
learning (artificial intelligence); pattern classification; support vector machines; text analysis; Chinese Web page classification test system; SVM-KNN algorithm; classifying prediction probability; feedback; k-nearest neighbor; support vector machine algorithm; text classification algorithm; Algorithm design and analysis; Classification algorithms; Prediction algorithms; Support vector machine classification; Text categorization; Training; Comparison of algorithms; KNN; SVM; text classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location
Beijing
ISSN
2327-0586
Print_ISBN
978-1-4799-3278-8
Type
conf
DOI
10.1109/ICSESS.2014.6933697
Filename
6933697
Link To Document