On generating near-optimal tableaux for conditional functional dependencies

Proceedings of the VLDB Endowment

Volumn 1, Issue 1, 2008, Pages 376-390

  Golab, Lukasz ^a   Karloff, Howard ^a   Korn, Flip ^a   Srivastava, Divesh ^a   Yu, Bei ^b  

^a AT AND T LABS RESEARCH   (United States)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

FINITE DIFFERENCE METHOD; POLYNOMIAL APPROXIMATION;

CONDITIONAL FUNCTIONAL DEPENDENCIES; DATA INCONSISTENCIES; GREEDY ALGORITHMS; INTEGRITY CONSTRAINTS; LARGE DATASETS; NEAR-OPTIMAL; POLYNOMIAL-TIME; RUNNING TIME;

OPTIMIZATION;

EID: 70349846180     PISSN: None     EISSN: 21508097     Source Type: Conference Proceeding    
DOI: 10.14778/1453856.1453900     Document Type: Article

References (22)

1. D. Agarwal, D. Barman, D. Gunopulos, N. Young, F. Korn, and D. Srivastava. Efficient and effective explanation of change in hierarchical summaries. In KDD, pp 6-15, 2007.
2. R. Agrawal, T. Imielinski, and A. Swami. Mining association rules between sets of items in large databases. In SIGMOD, pp 207-216, 1993.
3. P. Berman and M. Karpinski. On Some Tighter Inapproximability Results (Extended Abstract). In ICALP, pp. 200-209, 1999.
4. P. Bohannon, W. Fan, F. Geerts, X. Jia, and A. Kementsietsidis. Conditional functional dependencies for data cleaning. In ICDE, 2007.
5. L. Bravo, W. Fan, and S. Ma. Extending dependencies with conditions. In VLDB, 2007.
6. P. Brown, P. Haas. BHUNT: Automatic Discovery of Fuzzy Algebraic Constraints in Relational Data. In VLDB, 2003.
7. T. Calders, R. Ng, and J. Wijsen. Searching for dependencies at multiple abstraction levels. TODS, 27(3):229-260, 2002
8. S. Ceri, F. D. Guinta, and P. Lanzi. Mining constraint violations. TODS, 32(1), 2007.
9. G. Cong, W. Fan, F. Geerts, X. Jia, and S. Ma. Improving data quality: consistency and accuracy. In VLDB, 2007.
10. M. Dalkilic and E. Robertson. Information dependencies. In PODS, pp 245-253, 2000.
11. R. Gandhi, S. Khuller, and A. Srinivasan. Approximation algorithms for partial covering problems. J. Algorithms, 53(1):55-84, 2004.
12. M. R. Garey and D. S. Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness. Freeman, San Francisco, 1979.
13. C. Giannella and E. Robertson. On approximation measures for functional dependencies. Information Systems, 29(6):483-507, 2004.
14. Y. Huhtala, J. Karkkainen, P. Porkka, and H. Toivonen. Tane: An efficient algorithm for discovering functional and approximate dependencies. The Computer Journal, 42(2):100-111, 1999.
15. I. Ilyas, V. Markl, P. Haas, P. Brown, and A. Aboulnaga. Cords: Automatic discovery of correlations and soft functional dependencies. In SIGMOD, pp 647-658, 2004
16. M. J. Kearns and U. V. Vazirani. An introduction to computational learning theory. MIT Press, 1994.
17. R. King and J. Legendre. Discovery of functional and approximate functional dependencies in relational databases. Journal of Applied Mathematics and Decision Sciences, 7(1):49-59, 2003.
18. J. Kivinen and H. Mannila. Approximate inference of functional dependencies from relations. Theor. Comput. Sci., 149(1):129-149, 1995.
19. U. Nambiar and S. Kambhampati. Mining approximate functional dependencies and concept similarities to answer imprecise queries. In WebDB, 2004.
20. S. Sarawagi. Explaining differences in multidimensional aggregates. In VLDB, pp 42-53, 1999.
21. R. Srikant and R. Agrawal. Mining quantitative association rules in large relational tables. SIGMOD Rec., 25(2):1-12, 1996.
22. Y. Xu and R. Motwani. Random sampling based algorithms for efficient semi-key discovery. Stanford University Technical Report.