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@article{ART001096322},
author={Lee, Jae Yun},
title={Improving the Performance of SVM Text Categorization with Inter-document Similarities},
journal={Journal of the Korean Society for Information Management},
issn={1013-0799},
year={2005},
volume={22},
number={3},
pages={261-287},
doi={10.3743/KOSIM.2005.22.3.261}

TY - JOUR
AU - Lee, Jae Yun
TI - Improving the Performance of SVM Text Categorization with Inter-document Similarities
JO - Journal of the Korean Society for Information Management
PY - 2005
VL - 22
IS - 3
PB - 한국정보관리학회
SP - 261
EP - 287
SN - 1013-0799
AB - The purpose of this paper is to explore the ways to improve the performance of SVM(Support Vector Machines) text classifier using inter-document similarit ies. SVMs are powerful machine technique for automatic document classification. In this paper text categorization via SVMs aproach based on feature representation with document vectors is suggested. In this appr oach, document vectors instead stead of term weights are used as feature values. Experiments show that SVM clasifier with do cument vector features can improve the document classification performance. For the sake o f run-time efficiency, two methods are developed: One is to select document vector feature s, and the other is to use category centroid vector features instead. Experiments on these two methods show that we the performance of conventional methods with index term features.
KW - automatic document classification;text categorization;SVM classifier;classificationfeatures;document similarity
DO - 10.3743/KOSIM.2005.22.3.261
ER -

Lee, Jae Yun. (2005). Improving the Performance of SVM Text Categorization with Inter-document Similarities. Journal of the Korean Society for Information Management, 22(3), 261-287.

Lee, Jae Yun. 2005, "Improving the Performance of SVM Text Categorization with Inter-document Similarities", Journal of the Korean Society for Information Management, vol.22, no.3 pp.261-287. Available from: doi:10.3743/KOSIM.2005.22.3.261

Lee, Jae Yun "Improving the Performance of SVM Text Categorization with Inter-document Similarities" Journal of the Korean Society for Information Management 22.3 pp.261-287 (2005) : 261.

Lee, Jae Yun. Improving the Performance of SVM Text Categorization with Inter-document Similarities. 2005; 22(3), 261-287. Available from: doi:10.3743/KOSIM.2005.22.3.261

Lee, Jae Yun. "Improving the Performance of SVM Text Categorization with Inter-document Similarities" Journal of the Korean Society for Information Management 22, no.3 (2005) : 261-287.doi: 10.3743/KOSIM.2005.22.3.261

Lee, Jae Yun. Improving the Performance of SVM Text Categorization with Inter-document Similarities. Journal of the Korean Society for Information Management, 22(3), 261-287. doi: 10.3743/KOSIM.2005.22.3.261

Lee, Jae Yun. Improving the Performance of SVM Text Categorization with Inter-document Similarities. Journal of the Korean Society for Information Management. 2005; 22(3) 261-287. doi: 10.3743/KOSIM.2005.22.3.261

Lee, Jae Yun. Improving the Performance of SVM Text Categorization with Inter-document Similarities. 2005; 22(3), 261-287. Available from: doi:10.3743/KOSIM.2005.22.3.261

Lee, Jae Yun. "Improving the Performance of SVM Text Categorization with Inter-document Similarities" Journal of the Korean Society for Information Management 22, no.3 (2005) : 261-287.doi: 10.3743/KOSIM.2005.22.3.261