Word co-occurrence features for text classification

Information Systems

Volumn 36, Issue 5, 2011, Pages 843-858

  Figueiredo, Fábio ^a,b   Rocha, Leonardo ^c   Couto, Thierson ^d   Salles, Thiago ^b   Gonçalves, Marcos André ^b   Meira Jr , Wagner ^b  

^a EconoInfo Research   (Brazil)

^b FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

^c FEDERAL UNIVERSITY OF SÃO JOÃO DEL REI   (Brazil)

^d FEDERAL UNIVERSITY OF GOIÁS   (Brazil)

Author keywords

Classification; Feature extraction; Text mining

Indexed keywords

BAG OF WORDS; CLASSIFICATION; CLASSIFICATION ALGORITHM; CLASSIFICATION TASKS; DATA TREATMENT; DISCRIMINATIVE FEATURES; MULTI-CLASS; NEWSGROUPS; OHSUMED; TEXT CLASSIFICATION; TEXT COLLECTION; TEXT MINING; WORD CO-OCCURRENCE;

ALGORITHMS; DATA MINING; FEATURE EXTRACTION; INFORMATION RETRIEVAL SYSTEMS;

TEXT PROCESSING;

EID: 79955060532     PISSN: 03064379     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.is.2011.02.002     Document Type: Article

References (43)

1. F. Sebastiani Machine learning in automated text categorization ACM Computing Surveys 34 1 2002 1 47
2. D. Sculley, and G.M. Wachman Relaxed online svms for spam filtering SIGIR '07: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2007 ACM New York, NY, USA 415 422 (Pubitemid 350164988)
3. L. Zhang, J. Zhu, and T. Yao An evaluation of statistical spam filtering techniques ACM Transactions on Asian Language Information Processing (TALIP) 3 4 2004 243 269 (Pubitemid 40155221)
4. W.S. Rongbo Du, R. Safavi-Naini, Web filtering using text classification, 2003, pp. 325330.
5. L.C. Mohamed Hammami, D.V. Tsishkou, Adult content web filtering and face detection using data-mining based kin-color model 1, 2004, pp. 403406.
6. K. Chandrinos, I. Androutsopoulos, G. Paliouras, and C.D. Spyropoulos Automatic web rating: filtering obscene content on the web ECDL '00: Proceedings of the 4th European Conference on Research and Advanced Technology for Digital Libraries 2000 Springer-Verlag London, UK 403 406
7. T. Couto, M. Cristo, M.A. Gonçalves, P. Calado, N. Ziviani, E. Moura, and B. Ribeiro-Neto A comparative study of citations and links in document classification JCDL '06: Proceedings of the 6th ACM/IEEE-CS Joint Conference on Digital Libraries 2006 ACM New York, NY, USA 75 84 (Pubitemid 46609234)
8. G. Amati, D.D. Aloisi, V. Giannini, and F. Ubaldini A framework for filtering news and managing distributed data Journal of Universal Computer Science 3 8 1997 1007 1021 (Pubitemid 127825472)
9. T.M. Mitchell Does machine learning really work? AI Magazine 18 3 1997 11 20 (Pubitemid 127684648)
10. Y. Yang, and J.O. Pedersen A comparative study on feature selection in text categorization ICML '97: Proceedings of the 14th International Conference on Machine Learning 1997 Morgan Kaufmann Publishers Inc. San Francisco, CA, USA 412 420
11. G. Forman An extensive empirical study of feature selection metrics for text classification Journal of Machine Learning Research 3 2003 1289 1305
12. B. Possas, N. Ziviani, B. Ribeiro-Neto, and W. Meira Jr. The set-based model for information retrieval ACM Transactions on Information Systems 23 4 2005 397 429
13. R. Rak, W. Stach, O.R. Zaiane, M.L. Antonie, Considering re-occurring features in associative classifiers, in: PAKDD'05: 9th PacificAsia Conference on Knowledge Discovery and Data Mining, Hanoi, Vietnam, 2005, pp. 240248.
14. O.R. Zaiane, and M.L. Antonie Classifying text documents by associating terms with text categories CRPITS '02: Proceedings of the 13th Australasian Conference on Database Technologies 2002 Australian Computer Society, Inc. Darlinghurst, Australia 215 222
15. T. Joachims Making large-scale support vector machine learning practical Advances in Kernel Methods: Support Vector Learning 1999 MIT Press Cambridge, MA, USA 169 184
16. T. Joachims Training linear svms in linear time KDD '06: Proceedings of the 12th ACM SIGKDD: International Conference on Knowledge Discovery and Data Mining 2006 ACM Press Philadelphia, PA, USA 217 226 (Pubitemid 44535518)
17. P. Tan, M. Steinbach, and V. Kumar Introduction to Data Mining 2006 Addison-Wesley, Longman Publishing Co., Inc. Boston, MA, USA
18. D.D. Lewis, Representation and learning in information retrieval, Ph.D. Thesis, Amherst, MA, USA, 1992.
19. D.D. Lewis, Feature selection and feature extraction for text categorization, in: HLT '91: Proceedings of the Workshop on Speech and Natural Language, Association for Computational Linguistics, Morristown, NJ, USA, 1992, pp. 212217.
20. D.D. Lewis An evaluation of phrasal and clustered representations on a text categorization task SIGIR '92: Proceedings of the 15th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 1992 ACM New York, NY, USA 37 50
21. C. Apté, F. Damerau, and S.M. Weiss Automated learning of decision rules for text categorization ACM Transactions on Information Systems 12 3 1994 233 251
22. S. Dumais, J. Platt, D. Heckerman, and M. Sahami Inductive learning algorithms and representations for text categorization CIKM '98: Proceedings of the 7th International Conference on Information and Knowledge Management 1998 ACM New York, NY, USA 148 155
23. S. Scott, and S. Matwin Feature engineering for text classification ICML '99: Proceedings of the 16th International Conference on Machine Learning 1999 Morgan Kaufmann Publishers, Inc. San Francisco, CA, USA 379 388
24. D. Mladenić, M. Grobelnik, Word sequences as features in text-learning, in: Proceedings of ERK-98, the 7th Electrotechnical and Computer Science Conference, Ljubljana, SL, 1998, pp. 145148.
25. J. Fürnkranz, A study using n-gram features for text categorization, Technical Report, OEFAI-TR-9830, Austrian Institute for Artificial Intelligence, 1998.
26. G. Forman Feature selection for text classification Computational Methods of Feature Selection 2007 Chapman and Hall/CRC 257 276
27. M. F. Caropreso, S. Matwin, F. Sebastiani, A learner-independent evaluation of the usefulness of statistical phrases for automated text categorization, 2001, pp. 78102.
28. C.-M. Tan, Y.-F. Wang, and C.-D. Lee The use of bigrams to enhance text categorization Information Processing and Management 38 4 2002 529 546 (Pubitemid 34232114)
29. E. Crawford, I. Koprinska, J. Patrick, Phrases and feature selection in e-mail classification, in: P. Bruza, A. Moffat, A. Turpin (Eds.), ADCS, University of Melbourne, Department of Computer Science, 2004, pp. 5962. URL 〈 http://dblp.uni-trier.de/db/conf/adcs/adcs2004.html#CrawfordKP04 〉.
30. R. Bekkerman, J. Allan, Using bigrams in text categorization, Technical Report IR-408, Center of Intelligent Information Retrieval, UMass Amherst, 2004.
31. N. Chomsky, Syntactic Structures, The Houge, Mouton, The Netherlands, 1957.
32. A. Kaplan An experimental study of ambiguity and context Mechanical Translation 2 2 1955 39 46
33. Y. Choueka, and S. Lusignan Disambiguation by short contexts Computers and the Humanities 19 3 1985 147 157
34. J. Feng, H. Liu, J. Zou, Sat-mod: moderate itemset fittest for text classification, in: WWW '05: Special Interest Tracks and Posters of the 14th International Conference on World Wide Web, New York, NY, USA, 2005, pp. 10541055.
35. J.H.H. Cheng, X. Yan, C. Hsu, Discriminative frequent pattern analysis for effective classification, in: ICDE'07: Proceedings of 2007 International Conference on Data Engineering, Istanbul, Turkey, 2007, pp. 716725. (Pubitemid 47422075)
36. T. Mitchell Machine Learning 1997 McGraw-Hill New York, NY, USA
37. A.K. McCallum, Bow: a toolkit for statistical language modeling, text retrieval, classification and clustering, software available at URL 〈 http://www.cs.cmu.edu/∼mccallum/bow/ 〉, 1996.
38. V. Vapnik Statistical Learning Theory 1998 John Wiley & Sons Inc. New York, NY, USA
39. D.D. Lewis, Evaluating and optimizing autonomous text classification systems, in: SIGIR '95: Proceedings of the 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Seattle, Washington, USA, 1995, pp. 246254.
40. Y. Yang, and X. Liu A re-examination of text categorization methods Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR '99 1999 ACM New York, NY, USA 42 49
41. R. Jain The Art of Computer Systems Performance Analysis - Techniques for Experimental Design, Measurement, Simulation and Modeling 1991 John Wiley & Sons, Inc. New York, NY, USA
42. R. Tesar, V. Strnad, K. Jezek, and M. Poesio Extending the single words-based document model: a comparison of bigrams and 2-itemsets DocEng '06: Proceedings of the 2006 ACM Symposium on Document Engineering 2006 ACM New York, NY, USA 138 146 (Pubitemid 46634255)
43. R. Groeneveld An influence function approach to describing the skewness of a distribution The American Statistician 45 1991 97 102