Evolving explanatory novel patterns for semantically-based text mining

Natural Language Processing and Text Mining

Volumn , Issue , 2007, Pages 145-169

  Atkinson, John ^a  

^a UNIVERSITY OF CONCEPCIÓN   (Chile)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 79957663649     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-1-84628-754-1_9     Document Type: Chapter

References (35)

1. A. Bergstron, P. Jaksetic, and P. Nordin. Acquiring Textual Relations Automatically on the Web Using Genetic Programming. EuroGP 2000, Edinburgh, Scotland, pages 237-246, April 2000.
2. Michael Berry. Survey of Text Mining: Clustering, Classification, and Retrieval. Springer, 2004.
3. M. Berthold and D. Hand. Intelligent Data Analysis. Springer, 2000.
4. C. Coello. A Short Tutorial on Evolutionary Multiobjective Optimisation. ACM Computing Surveys, 2001.
5. Kalyanmoy Deb. Multi-objective Optimization Using Evolutionary Algorithms. Wiley, 2001.
6. U. Fayyad, G. Piatesky-Shapiro, and P. Smith. From Data Mining to Knowledge Discovery: An Overview. In Advances in Knowledge Discovery and Data Mining, pages 1-36. MIT Press, 1996.
7. R. Feldman. Knowledge Management: A Text Mining Approach. Proc. of the 2nd Int. Conference on Practical Aspects of Knowledge Management (PAKM98), Basel, Switzerland, October 1998.
8. R. Feldman and I. Dagan. Knowledge Discovery in textual databases (KDT). Proceedings of the first international conference on knowledge discovery and data mining (KDD-95), Montreal, Canada, pages 112-117, August 1995.
9. C. Fellbaum. Word Net: An Electronic Lexical Database. MIT Press, 1998.
10. P. Foltz, W. Kintsch, and T. Landauer. The Measurement of Textual Coherence with Latent Semantic Analysis. Discourse processes, 25(2):259-284, 1998.
11. C. Fonseca and P. Fleming. An Overview of Evolutionary Algorithms in Multiobjective Optimisation. Evolutionary Computation, 3(1):1-16, 1995.
12. A. Freitas. A Survey of Evolutionary Algorithms for Data Mining and Knowledge Discovery. Advances in Evolutionary Computation, Springer-Verlag, 2002.
13. D. Goldberg. Genetic Algorithms in Search, Optimization and Machine Learning. Addison Wesley, 1989.
14. J. Han and M. Kamber. Data Mining: Concepts and Techniques. Morgan-Kaufmann, 2001.
15. S. Harabagiu and D. Moldovan. Knowledge processing on an extended wordnet. In Word Net: An Electronic Lexical Database, pages 379-403. MIT Press, 1998.
16. M. Hearst. Automated Discovery of WordNet Relations. In Word Net: An Electronic Lexical Database, pages 131-151. MIT Press, 1998.
17. M. Hearst. Text Data Mining: Issues, Techniques and the Relation to Information Access. Technical report, Univerity of California at Berkeley, 1998.
18. M. Hearst. Untangling Text Data Mining. Proceedings of the 37th Annual Meeting of the ACL, University of Maryland (invited paper), June 1999.
19. M. Hearst. Text Mining Tools: Instruments for Scientific Discovery. IMA Text Mining Workshop, USA, April 2000.
20. C. Jacquemin and E. Tzoukermann. NLP for Term Variant Extraction: Synergy between Morphology, Lexicon, and Syntax. In Natural Language Information Retrieval. Kluwer Academic, 1999.
21. W. Kintsch. Predication. Cognitive Science, 25(2):173-202, 2001.
22. T. Landauer, P. Foltz, and D. Laham. An Introduction to Latent Semantic Analysis. Discourse Processes, 10(25):259-284, 1998.
23. C. Manning and H. Schutze. Foundations of Statistical Natural Language Processing. MIT Press, 1999.
24. M. Mitchell. An Introduction to Genetic Algorithms. MIT Press, 1996.
25. U. Nahm and R. Mooney. Using Information Extraction to Aid the Discovery of Prediction Rules from Text. Proceedings of the 6th International Conference on Knowledge Discovery and Data Mining (KDD-2000) Workshop on Text Mining, August 2000.
26. U. Nahm and R. Mooney. Text Mining with Information Extraction. AAAI 2002 Spring Symposium on Mining Answers from Texts and Knowledge Bases, Stanford, USA, 2002.
27. M. Rajman and R. Besancon. Text Mining: Knowledge Extraction from Unstructured Textual Data. 6th Conference of the International federation of classification societies (IFCS-98), Rome, Italy, July 1998.
28. P. Srinivasan. Text mining: Generating hypotheses from medline. Journal of the American Society for Information Science, 55(4):396-413, 2004.
29. W. Stadler. Fundamentals of Multicriteria Optimization. Plenum Press, New York, 1988.
30. D. Swanson. Migraine and Magnesium: Eleven Neglected Connections. Perspectives in Biology and Medicine, n/a(31):526-557, 1988.
31. D. Swanson. On the Fragmentation of Knowledge, the Connection Explosion, and Assembling Other People's ideas. Annual Meeting of the American Society for Information Science and Technology, 27(3), February 2001.
32. M. Weeber, H. Klein, L. de Jong, and R. Vos. Using concepts in literaturebased discovery: Simulating swanson's raynaud-fish oil and migraine-magnesium discoveries. Journal of the American Society for Information Science, 52(7):548-557, 2001.
33. P. Wiemer-Hastings. Adding Syntactic Information to LSA. Proceedings of the Twenty-second Annual Conference of the Cognitive Science Society, pages 989-993, 2000.
34. G. Williams. Evolutionary Hot Spots Data Mining. 3rd Pacific-Asia Conference, PAKDD-99, Beijing, China, April, pages 184-193, 1999.
35. E. Zitzler and L. Thiele. An Evolutionary Algorithm for Multiobjective Optimisation: The Strength Pareto Approach. Technical Report 43, Swiss Federal Institute of Technology (ETH), Switzerland, 1998.