Clustering categorical data: An approach based on dynamical systems

VLDB Journal

Volumn 8, Issue 3-4, 2000, Pages 222-236

  Gibson, David ^a   Kleinberg, Jon ^b   Raghavan, Prabhakar ^c  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b Department of Computer Science and School of Operations Research and Information Engineering   (United States)

^c IBM ALMADEN RESEARCH CENTER   (United States)

Author keywords

Categorial data; Clustering; Data mining; Dynamical systems; Hypergraphs

Indexed keywords

EID: 0034133769     PISSN: 10668888     EISSN: None     Source Type: Journal    
DOI: 10.1007/s007780050005     Document Type: Article

References (43)

1. Agrawal R, Mannila H, Srikant R, Toivonen H, Inkeri Verkamo A (1996) Fast Discovery of Association Rules. In: Fayyad UM, Piatetsky-Shapiro G, Smyth P, Uthurusamy R (eds.): Advances in Knowledge Discovery and Data Mining, chapter 12. MIT Press, Cambridge, Mass., pp. 307-328
2. Agrawal R, Imielinski T, Swami A (1993) Mining association rules between sets of items in large databases. In: Buneman P, Jajodia S (eds.): Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, Washington, D.C., May 26-28, 1993. ACM Press 1993, SIGMOD Record 22(2), June 1993, pages 207-216
3. Agrawal R, Srikant R (1994) Fast algorithms for mining association rules. In: Bocca JB, Jarke M, Zaniolo C (eds.): Proceedings of the 20th Internatinal Conference on Very Large Data Bases, (VLDB'94), September 12-15, 1994, Santiago de Chile, Chile. Morgan Kaufmann, ISBN 1-55860-153-8, pp. 487-499
4. Agresti A (1990) Categorical Data Analysis. Wiley-Interscience, Strasbourg
5. Alon N (1986) Eigenvalues and expanders. Combinatorica 6: 83-96
6. Alon N, Spencer J (1991) The Probabilistic Method. Wiley, Chichester
7. Berge C (1973) Hypergraphs. North-Holland, Amsterdam
8. Blum A, Spencer J (1995) Coloring random and semi-random k-colorable graphs. J Algorithms 19: 204-234
9. Boopana R (1987) Eigenvalues and graph bisection: An average-case analysis. In: Proc. IEEE Sympos. on Foundations of Computer Science, 1987, Los Angeles, Calofornia. IEEE Computer Society Press, publisher, pages 280-285
10. Brin S. Motwani R, Ullman JD, Tsur S (1997) Dynamic itemset counting and implication rules for market basket data. In: Peckham J (ed.): SIGMOD 1997, Proceedings ACM SIGMOD International Conference on Management of Data, May 13-15, ACM Press 1997, Tucson, Arizona, USA. SIGMOD Record 26(2), June 1997, pages 255-264
11. Brin S, Motwani R, Silverstein C (1997) Beyond Market Baskets: Generalizing Association Rules to Correlations. In: Peckham J (ed.): SIGMOD 1997, Proceedings ACM SIGMOD International Conference on Management of Data, May 13-15, ACM Press 1997, Tucson, Arizona, USA. SIGMOD Record 26(2), June 1997, pages 265-276
12. Brin S, Page L (1998) Anatomy of a Large-Scale Hypertextual Web Search Engine. In: Proc. 7th International WorldWide Web Conference, 1998,Brisbane, Australia, pp. 107-117. Elsevier, publisher.
13. Charniak E (1993) Statistical Language Learning. MIT Press, Cambridge, Mass.
14. Chiueh T (1994) Content-based image indexing. In: Bocca JB, Jarke M, Zaniolo C (eds.): Proceedings of the 20th Internatinal Conference on Very Large Data Bases, (VLDB'94), September 12-15, 1994, Santiago de Chile, Chile. Morgan Kaufmann, ISBN 1-55860-153-8, pp. 582-593
15. Chung FRK (1997) Spectral Graph Theory. AMS Press, Providence, R.I.
16. Das G, Mannila H, Ronkainen P (1998) Simliarity of attributes by external probes. In: Agrawal R, Stolorz PE, Piatetsky-Shapiro (eds.): Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), August 27-31, 1998, New York City, New York, USA. AAAI Press, 1998, ISBN, pages 23-29
17. Deerwester S, Dumais ST, Landauer TK, Furnas GW, Harshman RA (1990) Indexing by latent semantic analysis. J Soc Inf Sci 41(6): 391-407
18. Devaney RL (1989) An Introduction to Chaotic Dynamical Systems. Benjamin Cummings, New York
19. Donath WE, Hoffman AJ (1973) Lower bounds for the partitioning of graphs. IBM J Res Dev 17: 420-425
20. Duda RO, Hart PE (1973) Pattern Classiffcation and Scene Analysis. Wiley, New York
21. Faloutsos C (1996) Searching Multimedia Databases by Content. Kluwer Academic, Amsterdam
22. Fiedler M (1973) Algebraic connectivity of graphs. Czech Math J 23: 298-305
23. Flickner M, Sawhney H, Niblack W, Ashley J, Huang Q, Dom B, Gorkani M, Hafner J, Lee D, Petkovic D, Steele D, Yanker P (1995) Query by image and video content: The QBIC system. IEEE Comput 28: 23-32
24. Garey M, Johnson D (1979) Computers and Intractability: A Guide to the Theory of NP-Completeness. W.H. Freeman, New York
25. Golub G, Loan CF van (1989) Matrix Computations. Johns Hopkins University Press, Baltimore, Md.
26. Han E-H, Karypis G, Kumar V, Mobasher B (1997) Clustering Based On Association Rule Hypergraphs. In: Workshop on Research Issues on Data Mining and Knowledge Discovery, 1997, Tucson, Arizona, in conjunction with ACM SIGMOD 1997. ACM Press, publisher.
27. Hastie T, Stuetzle W (1989) Principal curves. J Am Stat Assoc 84: 502-516
28. Holm L, Sander C (1994)Proteins Struct Funct Genet 19: 256-268
29. Huang Z (1997) A Fast Clustering Algorithm to Cluster Very Large Categorical Data Sets in Data Mining. In: Workshop on Research Issues on Data Mining and Knowledge Discovery, 1997
30. Jerrum M, Sinclair A (1996) The Markov chain Monte Carlo method: An approach to approximate counting and integration. In: Hochbaum DS (ed) Approximation Algorithms for NP-hard Problems. PWS Publishing, Boston, Mass., pp. 482-520
31. Jolliffe IT (1986) Principal Component Analysis. Springer, Berlin Heidelberg New York
32. Kleinberg J (1997) Authoritative sources in a hyperlinked environment. IBM Research Report RJ 10076(91892). To appear in Journal of the ACM
33. Kohonen T (1982) Self-organized formation of topologically correct feature maps. Biol Cybern 43: 59-69
34. Kramer M (1991) Non-linear principal component analysis using auto-associative neural networks. AIChE J 37: 233-243
35. Mannila H, Toivonen H, Verkamo AI (1995) Discovering frequent episodes in sequences. In: Fayyad UM, Uthurusamy R (eds.): Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), Montreal, Canada, August 20-21, 1995. AAAI Press, ISBN 0-929280-82-2, pages 210-215
36. Ritter H, Martinetz T (1992) Neural Computation and Self-Organizing Maps. Addison-Wesley, Reading, Mass.
37. Rumelhart DE, McClelland JL (Eds) (1986) Parallel and Distributed Processing: Explorations in the Microstructure of Cognition. MIT Press, Cambridge, Mass.
38. Seiferas J (1999) A large bibliography on theory/foundations of computer science. Available at http://liinwww.ira.uka.de/ bibliography/Theory/Seiferas/Seiferas.html
39. Spielman D, Teng S (1996) Spectral partitioning works: Planar graphs and finite-element meshes. In: Proc. IEEE Symposium on Foundations of Computer Science, 1996, Burlington, Vermont. IEEE Computer Society Press, Piscataway, N.J., pp. 96-105
40. Srikant R, Agrawal R (1995) Mining generalized association rules. In: Dayal U, Gray PMD, Nishio S (eds.): Proceedings of 21th International Conference on Very Large Data Bases, September 11-15, 1995, Zurich, Switzerland. Morgan Kaufmann, ISBN 1-55860-379-4, pages 407-419
41. Toivonen H (1996) Sampling large databases for finding association rules. In: Vijayaraman TM, Buchmann AP, Mohan C, Sarda NL (eds.): VLDB'96, Proceedings of 22th International Conference on Very Large Data Bases, September 3-6, 1996, Mumbai (Bombay), India. Morgan Kaufmann 1996, ISBN 1-55860-382-4, pages 134-145
42. Wiederhold G (1999) Bibliography on database systems. Available at http://www.ira.uka.de/bibliography/Database/ Wiederhold/ Wiederhold. html
43. Zhang T, Ramakrishnan R, Livny M (1996) Birch: An effcient data-clustering method for very large databases. In: Jagadish HV, Mumick IS (eds.): Proceedings of the 1996 ACM SIGMOD International Conference on Management od Data, Montreal, Quebec, Canada, June 4-6, 1996. ACM Press 1996, SIGMOD Record 25(2), June 1996, pages 103-114