Citation: | Wang Deqing, Zhang Hui. Support-vector-based iteratively adjusted centroid classifier for text categorization[J]. Journal of Beijing University of Aeronautics and Astronautics, 2013, 39(2): 269-274. (in Chinese) |
[1] |
Sebastiani F.Machine learning in automated text categorization[J].ACM Computing Surveys,2002,34(1):1-47
|
[2] |
Wang D,Zhang H,Liu R,et al.Predicting bugs' components via mining bug reports[J].Journal of Software,2012,7(5): 1149-1154
|
[3] |
Han E H,Karypis G.Centroid-based document classification: analysis & experimental results[C]//Proceedings of PKDD'00.London:Springer-Verlag,2000:424-431
|
[4] |
Tam V,Santoso A,Setiono R.A comparative study of centroidbased,neighborhood-based and statistical approaches for effective document categorization[C]//Proceedings of 16th ICPR.Washington:IEEE Computer Society,2002:235-238
|
[5] |
Guan H, Zhou J,Guo M.A class-feature-centroid classifier for text categorization[C]//Proceedings of WWW.New York:ACM,2009:201-210
|
[6] |
Tan S.An improved centroid classifier for text categorization[J].Expert Systems with Applications,2008,35(1/2):1279-1285
|
[7] |
Tan S,Wang Y,Wu G.Adapting centroid classifier for document categorization[J].Expert Systems with Applications,2011, 38(8):10264-10273
|
[8] |
Lertnattee V,Theeramunkong T.Effect of term distributions on centroid-based text categorization[J].Information Sciences,2004,158:89-115
|
[9] |
Shankar S,Karypis G.Weight adjustment schemes for a centroid based classifier .TR 00-035,2000
|
[10] |
Foody G M.Issues in training set selection and refinement for classification by a feedforward neural network[C]//Proceedings of IGARSS.Seattle:IEEE,1998:409-411
|
[11] |
Cortes C,Vapnik V.Support-vector networks[J].Machine Learning,1995,20:273-297
|
[12] |
Joachims T.Text categorization with support vector machines .TR-23,University of Dortmund,1997
|
[13] |
Salton G,Buckley C.Term-weighting approaches in automatic text retrieval[J].Information Processing & Management,1988,24(5):513-523
|
[14] |
Jones K S.A statistical interpretation of term specificity and its application in retrieval[J].J Documentation,1972,28(1):11-21
|
[15] |
Han E H.Tmdata .Minnesota:University of Minnesota,2000 .http://www.cs.umn.edu/~han/data/tmdata.tar.gz
|
[16] |
Xiong H,Wu J,Chen J.K-means clustering versus validation measures:a data-distribution perspective[J].IEEE Transactions on Systems,Man,and Cybernetics Part B,2009,39(2):318-331
|
[17] |
Lewis D.Reuters-21578 .Dublin:Trinty College,2007 .
|
[18] |
Lang Ken.20Newsgroup .Massachusetts:Massachusetts Institute of Technology,2007 .
|
[19] |
Lewis D D.Evaluating and optimizing autonomous text classification systems[C]//Proceedings of 18th SIGIR.New York:ACM,1995:246-254
|
[20] |
Yu H,Hsieh C J,Chang K W,et al.Large linear classification when data cannot fit in memory[C]//Proceedings of KDD-10.New York:ACM,2010:833-842
|
[21] |
Yang Y,Liu X.A re-examination of text categorization methods[C]//Proceedings of SIGIR '99.New York:ACM,1999: 42- 49
|
[22] |
Chang C C,Lin C J.Libsvm:a library for support vector machines .Taiwan:Department of Computer Science and Information Engineering,National Taiwan University,2001 .http://www.csie.ntu.edu.tw/~cjlin/libsvm
|
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