Complex linguistic features for text classification: A comprehensive study

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2997, Issue , 2004, Pages 181-196

  Moschitti, Alessandro ^a   Basili, Roberto ^b  

^a The University of Texas at Dallas   (United States)

^b UNIVERSITY OF ROME TOR VERGATA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTATIONAL LINGUISTICS; LINGUISTICS; NATURAL LANGUAGE PROCESSING SYSTEMS; TEXT PROCESSING;

DOCUMENT REPRESENTATION; DOCUMENT RETRIEVAL; LINGUISTIC FEATURES; LINGUISTIC REPRESENTATIONS; NATURAL LANGUAGE PROCESSING; RETRIEVAL ACCURACY; TEXT CATEGORIZATION; TEXT CLASSIFICATION;

INFORMATION RETRIEVAL;

EID: 35048879815     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-24752-4_14     Document Type: Article

References (36)

1. Collins, M.: Three generative, lexicalized models for statistical parsing. In: Proceedings of the ACL and EACL, Somerset, New Jersey (1997) 16-23
2. Strzalkowski, T., Jones, S.: NLP track at TREC-5. In: Text REtrieval Conference. (1996)
3. Fellbaum, C.: WordNet: An Electronic Lexical Database. MIT Press. (1998)
4. Strzalkowski, T., Carballo, J.P.: Natural language information retrieval: TREC-6 report. In: TREC. (1997)
5. Strzalkowski, T., Stein, G.C., Wise, G.B., Carballo, J.P., Tapanainen, P., Jarvinen, T., Voutilainen, A., Karlgren, J.: Natural language information retrieval: TREC-7 report. In: TREC. (1998)
6. Strzalkowski, T., Carballo, J.P., Karlgren, J., Hulth, A., Tapanainen, P., Jarvinen, T.: Natural language information retrieval: TREC-8 report. In: TREC. (1999)
7. Smeaton, A.P.: Using NLP or NLP resources for information retrieval tasks. In Strzalkowski, T., ed.: Natural language information retrieval. Kluwer Academic Publishers, Dordrecht, NL (1999) 99-111
8. Sussua, M.: Word sense disambiguation for free-text indexing using a massive semantic network. In New York, A.P., ed.: Proceeding of CKIM 93. (1993)
9. Voorhees, E.M.: Using wordnet to disambiguate word senses for text retrieval. In: Proceedings of SIGIR 1993, PA, USA. (1993)
10. Voorhees, E.M.: Query expansion using lexical-semantic relations. In: Proceedings of SIGIR 1994. (1994)
11. Voorhees, E.M.: Using wordnet for text retrieval. In Fellbaum, C., ed.: WordNet: An Electronic Lexical Database, The MIT Press (1998) 285-303
12. Kilgarriff, A., Rosenzweig, J.: English senseval: Report and results. In: English SENSEVAL: Report and Results. In Proceedings of the 2nd International Conference on Language Resources and Evaluation, LREC, Athens, Greece. (2000)
13. Stokoe, G., Oakes, M.P., Tait, J.: Word sense disambiguation in information retrieval revisited. In: Proceedings of SIGIR03, Canada. (2003)
14. Furnkranz, J., Mitchell, T., Rilof, E.: A case study in using linguistic phrases for text categorization on the www. In: AAAI/ICML Workshop. (1998)
15. Mladenić, D., Grobelnik, M.: Word sequences as features in text-learning. In: Proceedings of ERK98, Ljubljana, SL (1998)
16. Raskutti, B., Ferrá, H., Kowalczyk, A.: Second order features for maximising text classification performance. In: Proceedings of ECML-01, 12th European Conference on Machine Learning, Springer Verlag, Heidelberg, DE (2001)
17. Bekkerman, R., El-Yaniv, R., Tishby, N., Winter, Y.: On feature distributional clustering for text categorization. In: Proceedings of the ACM SIGIR 2001, ACM Press (2001) 146-153
18. Tan, C.M., Wang, Y.F., Lee, C.D.: The use of bigrams to enhance text categorization. Information Processing & Management (2002)
19. Scott, S., Matwin, S.: Feature engineering for text classification. In: Proceedings of ICML-99, Bled, SL (1999)
20. Rocchio, J.: Relevance feedback in information retrieval. In G. Salton, editor, The SMART Retrieval System-Experiments in Automatic Document Processing, pages 313-323 Englewood Cliffs, NJ, Prentice Hall, Inc. (1971)
21. Basili, R., Moschitti, A., Pazienza, M.: NLP-driven IR: Evaluating performances over text classification task. In: Proceedings of IJCAI01, USA. (2001)
22. Moschitti, A.: A study on optimal parameter tuning for Rocchio text classifier. In Sebastiani, F., ed.: Proceedings of ECIR-03, 25th European Conference on Information Retrieval, Pisa, IT, Springer Verlag (2003)
23. Vapnik, V.: The Nature of Statistical Learning Theory. Springer (1995)
24. Joachims, T.: T. Joachims, making large-scale svm learning practical. In: Advances in Kernel Methods - Support Vector Learning. (1999)
25. Brill, E.: A simple rule-based part of speech tagger. In: Proc. of the Third Applied Natural Language Processing, Povo, Trento, Italy. (1992)
26. Basili, R., De Rossi, G., Pazienza, M.: Inducing terminology for lexical acquisition. In: Preoceeding of EMNLP 97 Conference, Providence, USA. (1997)
27. Salton, G., Buckley, C.: Term-weighting approaches in automatic text retrieval. Information Processing and Management 24(5) (1988) 513-523
28. Yang, Y.: An evaluation of statistical approaches to text categorization. Information Retrieval Journal (1999)
29. Caropreso, M.F., Matwin, S., Sebastiani, F.: A learner-independent evaluation of the usefulness of statistical phrases for automated text categorization. In: Idea Group Publishing, Hershey, US. (2001)
30. Lewis, D.D.: An evaluation of phrasal and clustered representations on a text categorization task. In: Proceedings of SIGIR-92, Kobenhavn, DK (1992)
31. Riloff, E.: Automatically generating extraction patterns from untagged text. In: AAAI/IAAI, Vol. 2. (1996) 1044-1049
32. Mitchell, T.: Machine Learning. McGraw Hill (1997)
33. Cohen, W.W., Singer, Y.: Context-sensitive learning methods for text categorization. ACM Transactions on Information Systems 17 (1999) 141-173
34. Furnkranz, J.: A study using n-gram features for text categorization. Technical report oefai-tr-9830, Austrian Institute for Artificial Intelligence. (1998)
35. Nigam, K., Lafferty, J., McCallum, A.: Using maximum entropy for text classification. In: IJCAI-99 Workshop. (1999)
36. Dumais, S.T., Platt, J., Heckerman, D., Sahami, M.: Inductive learning algorithms and representations for text categorization. In: Proceedings of CIKM-98, Bethesda, US, ACM Press, New York, US (1998) 148-155