Heuristic measures of interestingness

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

Volumn 1704, Issue , 1999, Pages 232-241

  Hilderman, Robert J ^a   Hamilton, Howard J ^a  

^a UNIVERSITY OF REGINA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

DATABASE SYSTEMS; PROBABILITY DISTRIBUTIONS;

HIGHLY-CORRELATED; INTERESTINGNESS; NEW APPLICATIONS; SAMPLE DATA;

DATA MINING;

EID: 22844455414     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-48247-5_25     Document Type: Conference Paper

References (23)

1. A.B. Atkinson. On the measurement of inequality. Journal of Economic Theory, 2:244–263, 1970.
2. W.H. Berger and F.L. Parker. Diversity of planktonic forminifera in deep-sea sediments. Science, 168:1345–1347, 1970.
3. I. Bournaud and J.-G. Ganascia. Accounting for domain knowledge in the construction of a generalization space. In Proceedings of the Third International Conference on Conceptual Structures, pages 446–459. Springer-Verlag, August 1997.
4. J.R. Bray and J.T. Curtis. An ordination of the upland forest communities of southern Wisconsin. Ecological Monographs, 27:325–349, 1957.
5. A.A. Freitas. On objective measures of rule surprisingness. In J. Zytkow and M. Quafafou, editors, Proceedings of the Second European Conference on the Principles of Data Mining and Knowledge Discovery (PKDD’98), pages 1–9, Nantes, France, September 1998.
6. R. Godin, R. Missaoui, and H. Alaoui. Incremental concept formation algorithms based on galois (concept) lattices. Computational Intelligence, 11(2):246–267, 1995.
7. H.J. Hamilton, R.J. Hilderman, L. Li, and D.J. Randall. Generalization lattices. In J. Zytkow and M. Quafafou, editors, Proceedings of the Second European Conference on the Principles of Data Mining and Knowledge Discovery (PKDD’98), pages 328–336, Nantes, France, September 1998.
8. R.J. Hilderman and H.J. Hamilton. Heuristics for ranking the interestingness of discovered knowledge. In N. Zhong and L. Zhou, editors, Proceedings of the Third Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’99), pages 204–209, Beijing, China, April 1999.
9. R.J. Hilderman, H.J. Hamilton, and B. Barber. Ranking the interestingness of summaries from data mining systems. In Proceedings of the 12th International Florida Artificial Intelligence Research Symposium (FLAIRS’99), pages 100–106, Orlando, Florida, May 1999.
10. R.J. Hilderman, H.J. Hamilton, R.J. Kowalchuk, and N. Cercone. Parallel knowledge discovery using domain generalization graphs. In J. Komorowski and J. Zytkow, editors, Proceedings of the First European Conference on the Principles of Data Mining and Knowledge Discovery (PKDD’97), pages 25–35, Trondheim, Norway, June 1997.
11. S. Kullback and R.A. Leibler. On information and sufficiency. Annals of Mathematical Statistics, 22:79–86, 1951.
12. H. Liu, H. Lu, and J. Yao. Identifying relevant databases for multidatabase mining. In X. Wu, R. Kotagiri, and K. Korb, editors, Proceedings of the Second Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’98), pages 210–221, Melbourne, Australia, April 1998.
13. R.H. MacArthur. Patterns of species diversity. Biological Review, 40:510–533, 1965.
14. R.P. McIntosh. An index of diversity and the relation of certain concepts to diveristy. Ecology, 48(3):392–404, 1967.
15. W.A. Rosenkrantz. Introduction to Probability and Statistics for Scientists and Engineers. McGraw-Hill, 1997.
16. R.R. Schutz. On the measurement of income inequality. American Economic Review, 41:107–122, March 1951.
17. C.E. Shannon and W. Weaver. The mathematical theory of communication. University of Illinois Press, 1949.
18. E.H. Simpson. Measurement of diversity. Nature, 163:688, 1949.
19. G. Stumme, R. Wille, and U. Wille. Conceptual knowledge discovery in databases using formal concept analysis methods. In J. Zytkow and M. Quafafou, editors, Proceedings of the Second European Conference on the Principles of Data Mining and Knowledge Discovery (PKDD’98), pages 450–458, Nantes, France, September 1998.
20. H. Theil. Economics and information theory. Rand McNally, 1970.
21. R.H. Whittaker. Evolution and measurement of species diversity. Taxon, 21 (2/3):213–251, May 1972.
22. Y.Y. Yao, S.K.M. Wong, and C.J. Butz. On information-theoretic measures of attribute importance. In N. Zhong and L. Zhou, editors, Proceedings of the Third Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’99), pages 133–137, Beijing, China, April 1999.
23. J.F. Young. Information theory. John Wiley & Sons, 1971.