Rough set feature selection algorithms for textual case-based classification

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

Volumn 4106 LNAI, Issue , 2006, Pages 166-181

  Gupta, Kalyan Moy ^a   Aha, David W ^b   Moore, Philip ^c  

^a KNEXUS RESEARCH CORPORATION   (United States)

^b NAVAL RESEARCH LABORATORY   (United States)

^c ITT INDUSTRIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTATIONAL COMPLEXITY; DATA STRUCTURES; FEATURE EXTRACTION; INFORMATION RETRIEVAL; KNOWLEDGE BASED SYSTEMS;

CASE BASED CLASSIFICATION; DATA SET; ROUGH SET ALGORITHMS;

ALGORITHMS;

EID: 33751006443     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11805816_14     Document Type: Conference Paper

References (20)

1. An, A., Huang, Y., Huang, X., & Cercone, N. (2004). An effective rough set-based method for text classification. Transactions on Rough Sets, 2, 1-13.
2. Brill, E. (1993). A corpus-based approach to language learning. Doctoral dissertation: Department of Computer Science, University of Pennsylvania, Philadelphia, PA.
3. Bruninghaus, S. & Ashley, K.D. (2003). Combining case-based and model-based reasoning for predicting the outcome of legal cases. Proceedings of the Fifth International Conference on Case-Based Reasoning (pp. 65-79). Trondheim, Norway: Springer.
4. Chouchoulas, A., & Shen, Q. (2001). Rough-set aided keyword reduction for text categorization. Applied Artificial Intelligence, 15, 843-873.
5. Delany, S.J., Cunningham, P., Doyle D., & Zamolokskikh, A. (2005). Generating estimates of classification confidence for a case-based spam filter. Proceedings of the Sixth International Conference on Case-Based Reasoning (pp. 177-190), Chicago, IL: Springer.
6. Gupta, K.M, & Aha, D.W.(2004). RuMop: A rule-based morphotactic parser. Proceedings of the International Conference on Natural Language Processing (pp. 280-284). Hyderabad, India: Allied Publishers.
7. Gupta, K.M., Moore, P.G., Aha, D.W., & Pal, S.K. (2005). Rough set feature selection methods for case-based categorization of text documents. Proceedings of the First International Conference on Pattern Recognition and Machine Intelligence (pp. 792-798). Kolkata, India: Springer.
8. Johnson, D.S. (1974). Approximation algorithms for combinatorial problems, Journal of Computer and System Sciences, 9, 256-278.
9. Lang, K. (2006). 20 News group dataset. [http://www.cs.cmu.edu/afs/cs. cmu.edu/project/theo-20/www/data/news20.html]
10. Li, Y., Shiu, S.C.K., & Pal, S. (2006). Combining Feature Reduction and Case Selection in Building CBR Classifiers. In D.W. Aha, K.M. Gupta, & S.K. Pal (Eds.) Case-Based Reasoning and Data Mining. Hoboken, NJ: John Wiley & Sons.
11. Montazemi, A.R. & Gupta, K.M. (1997). A framework for retrieval in case-based reasoning systems. Annals of operations research, 72, 51-73.
12. Pal, S.K., & Shiu, S.C.K. (2004). Foundations of soft case-based reasoning. Hoboken, NJ: Wiley.
13. Pawlak, Z. (1991). Rough sets. Norwell, MA: Kluwer Academic Publishers.
14. Quirk, R., Greenbaum, S., Leech, G., & Svartvik, J. (1985). A comprehensive grammar of the English language. New York, NY: Longman.
15. Reuters (2006). Reuters-21578 Evaluation Data. Retrieved on April, 12, 2005 from [http://www.daviddlewis.com/resources/testcollections/reuters21578/]
16. Skowron, A., (1995). Extracting laws from decision tables. Computational Intelligence, 11(2), 371-388.
17. Weber, R.O., Ashley, K.D., & Bruninghaus, S. (2005). Textual case-based reasoning. To appear in Knowledge Engineering Review, 20(3).
18. Wilson, D.C., & Bradshaw, S. (2000). CBR textuality. Expert Update, 3(1), 28-37.
19. Wiratunga, N., Koychev, I., & Massie, S. (2004). Feature selection and generalization for retrieval of textual cases. Proceedings of the Seventh European Conference on Case-Based Reasoning (pp. 806-820). Madrid, Spain: Springer.
20. Yang, Y., & Pederson, J. (1997). A comparative study of feature selection in text categorization. Proceedings of the Fourteenth International Conference on Machine Learning (pp. 412-420). Nashville, TN: Morgan Kaufmann.