Title :
Research on text classification based on SVM-KNN
Author :
Yun Lin ; Jie Wang
Author_Institution :
Capital Normal Univ., Beijing, China
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;
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-3278-8
DOI :
10.1109/ICSESS.2014.6933697
