References
- F. Sebastiani, "Machine learning in automated text categorization," ACM Computing Surveys, vol. 34, no. 1, pp. 1-47, Mar. 2002. https://doi.org/10.1145/505282.505283
- Y. Yang and J. O. Pedersen, "A comparative study on feature selection in text categorization," Proceedings of the 14th International Conference on Machine Learning, Nashville, TN, 1997, pp. 412-420.
- Y. Ko and J. Seo, "Automatic text categorization by unsupervised learning," Proceedings of the 18th Conference on Computational Linguistics, Saarbrucken, Germany, 2000, pp. 453-459. https://doi.org/10.3115/990820.990886
- A. McCallum and K. Nigam, "A comparison of event models for naive bayes text classification," AAAI/ICML Workshop on Learning for Text Categorization, Madison, WI, 1998, pp. 41-48.
- D. D. Lewis, R. E. Schapire, J. P. Callan, and R. Papka, "Training algorithms for linear text classifiers," Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Zurich, Switzerland, 1996, pp. 298-306. https://doi.org/10.1145/243199.243277
- Y. Yang, S. Slattery, and R. Ghani, "A study of approaches to hypertext categorization," Journal of Intelligent Information Systems, vol. 18, no. 2-3, pp. 219-241, Mar. 2002. https://doi.org/10.1023/A:1013685612819
- T. Joachims, "Learning to classify text using support vector machines," Ph.D. dissertation, University of Dortmund, Dormnund, 2001.
- Y. Ko and J. Seo, "Text classification from unlabeled documents with bootstrapping and feature projection techniques," Information Processing and Management, vol. 45, no. 1, pp. 70-83, Jan. 2009. https://doi.org/10.1016/j.ipm.2008.07.004
- N. Slonim, N. Friedman, and N. Tishby, "Unsupervised document classification using sequential information maximization," Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Tampere, Finland, 2002, pp. 129-136. https://doi.org/10.1145/564376.564401
- H. Han, Y. Ko, and J. Seo, "Using the revised EM algorithm to remove noisy data for improving the one-against-the-rest method in binary text classification," Information Processing and Management, vol. 43, no. 5, pp. 1281-1293, Sep. 2007. https://doi.org/10.1016/j.ipm.2006.11.003
- Y. Ko and J. Seo, "Using the feature projection technique based on a normalized voting method for text classification," Information Processing and Management, vol. 40, no. 2, pp. 191-208, Mar. 2004. https://doi.org/10.1016/S0306-4573(03)00029-3
- Y. Ko, J. Park, and J. Seo, "Improving text categorization using the importance of sentences," Information Processing and Management, vol. 40, no. 1, pp. 65-79, Jan. 2004. https://doi.org/10.1016/S0306-4573(02)00056-0
- K. Nigam, A. McCallum, and T. Mitchell, "Semi-supervised text classification using EM," Semi-Supervised Learning, Cambridge, MA: MIT Press, pp. 33-56, 2006.
- S. Tong and D. Koller, "Support vector machine active learning with applications to text classification," Journal of Machine Learning Research, vol. 2, pp. 45-66, Nov. 2001. https://doi.org/10.1162/153244302760185243
- E. Brill, "Transformation-based error-driven learning and natural language processing: a case study in part-of-speech tagging," Computational Linguistics, vol. 21, no. 4, pp. 543-565, Dec. 1995.
- Y. S. Maarek, D. M. Berry, and G. E. Kaiser, "An information retrieval approach for automatically constructing software libraries," IEEE Transactions on Software Engineering, vol. 17, no. 8, pp. 800-813, Aug. 1991. https://doi.org/10.1109/32.83915
- Y. Karov and S. Edelman, "Similarity-based word sense disambiguation," Computational Linguistics, vol. 24, no. 1, pp. 41-59, Mar. 1998.
- M. Craven, D. Dipasquo, D. Freitag, A. McCallum, T. Mitchell, K. Nigam, and S. Slattery, "Learning to construct knowledge bases from the World Wide Web," Artificial Intelligence, vol. 118, no. 1-2, pp. 69-113, Apr. 2000. https://doi.org/10.1016/S0004-3702(00)00004-7
- Y. Yang, "An evaluation of statistical approaches to text categorization," Information Retrieval, vol. 1, no. 1-2, pp. 69-90, 1999. https://doi.org/10.1023/A:1009982220290
- T. Joachims, "A probabilistic analysis of the Rocchio algorithm with TFIDF for text categorization," Proceedings of the Fourteenth International Conference on Machine Learning, Nashville, TN, 1997, pp. 143-151.
- T. Joachims, Learning to Classify Text Using Support Vector Machines, Boston: Kluwer Academic Publishers, 2002.
- B. Zadrozny and C. Elkan, "Obtaining calibrated probability estimates from decision trees and naïve Bayesian classifiers," Proceedings of the Eighteenth International Conference on Machine Learning, Williamstown, MA, 2001, pp. 609-616.
- B. Zadrozny and C. Elkan, "Transforming classifier scores into accurate multiclass probability estimates," Proceedings of the Eight ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Edmonton, AB, 2002, pp. 694-699. https://doi.org/10.1145/775047.775151
- C. W. Hsu and C. J. Lin, "A comparison of methods of multi-class support vector machines," IEEE Transactions on Neural Networks, vol. 13, no. 2, pp. 415-425, Mar. 2002. https://doi.org/10.1109/72.991427
- D. D. Lewis, "Naive (bayes) at forty: the independence assumption in information retrieval," Proceedings of the 10th European Conference on Machine Learning, Chemnitz, Germany, 1998, pp. 4-15. https://doi.org/10.1007/BFb0026666
- C. H. Lee, C. R. Lin, and M. S. Chen, "Sliding-window filtering: an efficient algorithm for incremental mining," Proceedings of the ACM CIKM: 10th International Conference on Information and Knowledge Management, Atlanta, GA, 2001, pp. 263-270. https://doi.org/10.1145/502585.502630
- T. M. Mitchell, Machine Learning, New York: McGraw-Hill, 1997.
- A. P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum likelihood from incomplete data via em algorithm," Journal of the Royal Statistical Society Series B-Methodological, vol. 39, no. 1, pp. 1-38, 1977. https://doi.org/10.2307/2984875
- T. Joachims, "Text categorization with support vector machines: learning with many relevant features," Machine Learning: ECML-98. Lecture Notes in Computer Science vol. 1398, Heidelberg: Springer Verlag, pp. 137-142, 2002. https://doi.org/10.1007/BFb0026683
- G. Salton and C. Buckley, "Term-weighting approaches in automatic text retrieval," Information Processing and Management, vol. 24, no. 5, pp. 513-523, 1988. https://doi.org/10.1016/0306-4573(88)90021-0
- B. Endres-Niggemeyer, Summarizing Information, New York: Springer, pp. 307-338, 1998.
Cited by
- Cross-Lingual Annotation Projection for Weakly-Supervised Relation Extraction vol.13, pp.1, 2014, https://doi.org/10.1145/2529994