원문정보
보안공학연구지원센터(IJMUE)
International Journal of Multimedia and Ubiquitous Engineering
Vol.10 No.4
2015.04
pp.283-290
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
This paper mainly explores the use of Support Vector Machines (SVMs) for Uyghur text classification, presents the process of text categorization: Text preprocessing, feature dimensionality reduction, representation method and classification of text features etc., discusses the SVMs classification algorithm in the application of Uyghur text classification. Focus on the construction of text categorization model and its procedures. Experiment results show that training by using the selected training data with the guarantee of the performance of the classifier, has higher efficiency than other nearest neighbor classifier (KNN), Naive Bayes (NB) classifier with increased accuracy.
목차
Abstract
1. Introduction
2. Text Categorization
3. Main Title
3.1 The Features of Uyghur Language
3.2 Pre-processing of Uyghur Texts
3.3 Feature Selection
4. The SVM based Text Classification Algorithm
5. Experimental Results and Analysis
5.1 Experimental Corpus
5.2 Experimental Environment
5.3 Results of Classification based on the SVM
5.4 Comparison Results of SVM, KNN and NB
6. Conclusions
Acknowledgements
References
1. Introduction
2. Text Categorization
3. Main Title
3.1 The Features of Uyghur Language
3.2 Pre-processing of Uyghur Texts
3.3 Feature Selection
4. The SVM based Text Classification Algorithm
5. Experimental Results and Analysis
5.1 Experimental Corpus
5.2 Experimental Environment
5.3 Results of Classification based on the SVM
5.4 Comparison Results of SVM, KNN and NB
6. Conclusions
Acknowledgements
References
저자정보
참고문헌
자료제공 : 네이버학술정보