Closed set based discovery of representative association rules

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

Volumn 2189, Issue , 2001, Pages 350-359

  Kryszkiewicz, Marzena ^a  

^a WARSAW UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

DATA HANDLING; INFORMATION ANALYSIS;

CLOSED ITEMSETS; CLOSED SET; COVER OPERATORS; LARGE DATABASE; LOSSLESS; MINING PROBLEMS;

ASSOCIATION RULES;

EID: 84958543833     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44816-0_35     Document Type: Conference Paper

References (14)

1. Agrawal, R., Imielinski, T., Swami, A.: Mining associations rules between sets of items in large databases. In: Proc. of the ACM SIGMOD Conference on Management of Data. Washington (1993) 207–216
2. Agrawal, R., Mannila, H., Srikant, R., Toivonen, H., Verkamo, A.I.: Fast discovery of association rules. In: Advances in Knowledge Discovery and Data Mining. AAAI, Menlo Park (1996) 307–328
3. Boulicaut, J.F., Bykowski, A.: Frequent closures as a concise representation for binary data mining. In: Proc. of PAKDD’00, Kyoto. LNAI 1805. Springer-Verlag (2000) 62–73
4. Kryszkiewicz, M.: Representative association rules. In: Proc. of PAKDD’98. Melbourne. LNAI 1394. Springer-Verlag (1998) 198–209
5. Kryszkiewicz, M.: Fast Discovery of representative association rules. In: Proc. of RSCTC’98. Warsaw. LNAI 1424. Springer-Verlag (1998) 214–221
6. Kryszkiewicz M.: Representative association rules and minimum condition maximum consequence association rules. In: Proc. of PKDD’98. Nantes. LNAI 1510. Springer-Verlag (1998) 361–369
7. Meo, R., Psaila, G., Ceri, S.: A New SQL-like operator for mining association rules. In: Proc. of the 22nd VLDB Conference. Mumbai (1996) 122–133
8. Pasquier N., Bastide Y., Taouil R., Lakhal L.: Efficient mining of association rules using closed itemset lattices. Information Systems 24 (1999) 25–46
9. Pasquier, N.: Algorithmes d’extraction et de réduction des régles d’association dans les bases de données. These de Doctorat. Univ. Pascal-Clermont-Ferrand II (2000)
10. Pei, J., Han, J., Mao, R.: CLOSET: An efficient algorithm for mining frequent closed itemsets. In: Proc. of the ACM SIGMOD DMKD’00. Dallas (2000) 21–30
11. Piatetsky-Shapiro, G.: Discovery, analysis and presentation of strong rules. In: Piatetsky-Shapiro, G., Frawley, W. (eds.): Knowledge Discovery in Databases. AAAI/MIT Press (1991) 229–248
12. Saquer J., Deogun, J.S.: Using Closed itemsets for discovering representative association rules. In: Proc. of ISMIS’00. Charlotte. LNAI 1932. Springer-Verlag (2000) 495–504
13. Srikant, R., Agrawal, R.: Mining generalized association rules. In: Proc. of the 21st VLDB Conference. Zurich (1995) 407–419
14. Walczak, Z.: Selected problems and algorithms of data Mining. M.Sc. Thesis. Warsaw University of Technology (1998)