Average number of frequent (closed) patterns in Bernouilli and Markovian databases

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2005, Pages 713-716

  Lhote, Loïck ^a   Rioult, François ^a   Soulet, Arnaud ^a  

^a UNIVERSITÉ DE CAEN   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATION RULES; DATABASE SYSTEMS; MARKOV PROCESSES; MATHEMATICAL MODELS; POLYNOMIAL APPROXIMATION; PROBABILITY DISTRIBUTIONS;

ASSOCIATION RULES DISCOVERY; AVERAGE ANALYSIS; PROBABILISTIC MODELS;

DATA MINING;

EID: 34548553139     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2005.31     Document Type: Conference Paper

References (14)

1. R. Agrawal, H. Mannila, R. Srikant, H. Toivonen, and A. Verkamo. Fast discovery of association rules. In Advances in Knowledge Discovery and Data Mining, pages 307-328, 1996.
2. R. Agrawal and R. Srikant. Fast algorithms for mining association rules. In International Conference on Very Large Data Bases (VLDB'94), Santiago de Chile, pages 487-499, 1994.
3. H. Fu and E. Mephu Nguifo. How well go lattice algorithms on currently used machine learning testbeds ? In First International. Conference on Formal. Concept Analysis, 2003.
4. F. Geerts, B. Goethals, and J. Van den Bussche. A tight upper bound on the number of candidate patterns. In ICDM, pages 155-162, 2001.
5. D. Gunopulos, H. Mannila, R. Khardon, and H. Toivonen. Data mining, hypergraph transversals, and machine learning. In PODS 1997, pages 209-216, 1997.
6. D. Gunopulos, H. Mannila, and S. Saluja. Discovering all most specific sentences by randomized algorithms. In ICDT, pages 215-229, 1997.
7. S. O. Kuznetsov and S. A. Obiedkov. Comparing performance of algorithms for generating concept lattices. Journal of Experimental, and Theoretical Artificial Intelligence, 14(2-3): 189-216, 2002.
8. L. Lhote, F. Rioult, and A. Soulet. Average number of frequent and closed patterns in random databases. In Conférence d'Apprentissage, CAp'05, pages 345-360, 2005.
9. L. Lhote, F. Rioult, and A. Soulet. Average number of frequent and closed patterns in random databases. In Technical Report, Université de Caen, 2005.
10. P. W. Purdom, D. V. Gucht, and D. P. Groth. Average-case performance of the apriori algorithm. SIAM Journal on Computing, 33(5): 1223-1260, 2004.
11. R. Srikant and R. Agrawal. Mining quantitative association rules in large relational tables. In Proceedings of the 1996 ACM SIGMOD international conference on Management of data, pages 1-12. ACM Press, 1996.
12. H. Toivonen. Sampling large databases for association rules. In International Conference on Very Large Data Bases, pages 134-145. Morgan Kaufman, 1996.
13. R. Wille. Concept lattices and conceptual knowledge systems. In Computer mathematic applied, 23(6-9):493-515, 1992.
14. M. J. Zaki. Generating non-redundant association rules. In SIGKDD'00, Boston, pages 34-43, 2000.