Title :
Research on methodology of document classification based on statistical learning theory
Author_Institution :
Coll. of Software, Zhejiang Univ. of Technol., Hangzhou, China
Abstract :
Document classification is one of important steps in document mining. With the statistical learning theory, they proposed a kind of machine learning method based on small sample set. This paper presents a kind of classification model for document classification based on statistical learning theory. In this model, we adopt organized vectors as the eigenvector of documents, trains classifier by means of SVM algorithm, and obtain satisfactory experiment results.
Keywords :
classification; data mining; document handling; eigenvalues and eigenfunctions; learning (artificial intelligence); statistical analysis; support vector machines; SVM algorithm; data mining; document classification; document mining; machine learning; organized vectors; statistical learning theory; support vector machine; Data mining; Educational institutions; Learning systems; Machine learning; Machine learning algorithms; Statistical analysis; Statistical learning; Support vector machine classification; Support vector machines; Text categorization;
Conference_Titel :
Services Systems and Services Management, 2005. Proceedings of ICSSSM '05. 2005 International Conference on
Print_ISBN :
0-7803-8971-9
DOI :
10.1109/ICSSSM.2005.1500167
