Mining frequent conjunctive queries in star schemas

ACM International Conference Proceeding Series

Volumn , Issue , 2009, Pages 97-108

  Jen, Tao Yuan ^a   Laurent, Dominique ^a   Spyratos, Nicolas ^b  

^a UNIVERSITÉ DE CERGY PONTOISE   (France)

^b CNRS   (France)

Author keywords

Frequent queries; Functional dependencies; Inclusion dependencies; Query comparison

Indexed keywords

CONJUNCTIVE QUERIES; EQUIVALENCE RELATIONS; FOREIGN KEYS; FREQUENT QUERIES; FUNCTIONAL DEPENDENCIES; INCLUSION DEPENDENCIES; QUERY COMPARISON; RELATIONAL DATABASE; SCHEMAS; STAR SCHEMA;

COMPUTATION THEORY; SET THEORY;

QUERY LANGUAGES;

EID: 70350675551     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1620432.1620443     Document Type: Conference Paper

References (16)

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 309-328. AAAI-MIT Press, 1996.
2. W. Armstrong. Dependency structures of data base relationships. In IFIP Congress, pages 580-583. North Holland, 1974.
3. L. Copin, N. Pecheur, A. Laurent, Y. Augusta, B. Sentana, D. Laurent, and T.-Y. Jen. Dbfrequentqueries: Extraction de requêtes fréquentes. In EGC, volume RNTI-E-15 of Revue des Nouvelles Technologies de l'Information, page 499. Cépaduès-Éditions, 2009.
4. L. Dehaspe and L. D. Raedt. Mining association rules in multiple relations. In 7th International Workshop on Inductive Logic Programming, volume 1297 of LNCS, pages 125-132. Springer Verlag, 1997.
5. C. Diop, A. Giacometti, D. Laurent, and N. Spyratos. Composition of mining contexts for efficient extraction of association rules. In EDBT'02, volume 2287 of LNCS, pages 106-123. Springer Verlag, 2002.
6. B. Goethals and J. V. den Bussche. Relational association rules: getting warmer. In ESF Exploratory Workshop on Pattern Detection and Discovery in Data Mining, volume 2447 of LNCS, pages 125-139. Springer-Verlag, 2002.
7. B. Goethals, E. Hoekx, and J. V. den Bussche. Mining tree queries in a graph. In 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 61-69, 2005.
8. B. Goethals, W. L. Page, and H. Mannila. Mining association rules of simple conjunctive queries. In SIAM, 2008.
9. J. Han, Y. Fu, W. Wang, K. Koperski, and O. Zaiane. Dmql : A data mining query language for relational databases. In SIGMOD-DMKD'96, pages 27-34, 1996.
10. J. Han, J. Pei, Y. Yin, and R. Mao. Mining frequent patterns without candidate generation: A frequent-pattern tree approach. Data Mining and Knowledge Discovery, 8:53-87, 2004.
11. T. Jen, D. Laurent, and N. Spyratos. Mining all frequent selection-projection queries from a relational table. In EDBT'08, pages 368-379. ACM Press, 2008.
12. T. Jen, D. Laurent, N. Spyratos, and O. Sy. Towards mining frequent queries in star schemes. In International Workshop on Knowledge Discovery in Databases (KDID), volume 3933 of LNCS, pages 104-123. Springer Verlag, 2005.
13. T. Jen, R. Taouil, and D. Laurent. A dichotomous algorithm for association rule mining. In International workshop Grid and Peer-to-Peer Computing Impacts on Large Scale Heterogeneous Distributed Database Systems (GLOBE), in conjunction with intl. conf. DEXA, pages 567-571. IEEE Press, 2004.
14. D. S. Johnson and A. C. Klug. Testing containment of conjunctive queries under functional and inclusion dependencies. In PODS, pages 164-169, 1982.
15. R. Meo, G. Psaila, and S. Ceri. An extension to sql for mining association rules. Data Mining and Knowledge Discovery, 9:275-300, 1997.
16. J. Ullman. Principles of Databases and Knowledge-Base Systems, volume 1. Computer Science Press, 1988.