Approximate lineage for probabilistic databases

Proceedings of the VLDB Endowment

Volumn 1, Issue 1, 2008, Pages 797-808

  Ré, Christopher ^a   Suciu, Dan ^a  

^a University of Washington   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATABASE SYSTEMS; ERROR ANALYSIS; POLYNOMIAL APPROXIMATION; QUERY PROCESSING;

BOOLEAN EXPRESSIONS; BOOLEAN FORMULAE; FOURIER APPROXIMATIONS; HIGHER COMPRESSION RATIOS; LARGE DATABASE; PROBABILISTIC DATABASE; PUBLIC DATABASE; REAL DATA SETS;

BOOLEAN ALGEBRA;

EID: 79952758877     PISSN: None     EISSN: 21508097     Source Type: Conference Proceeding    
DOI: 10.14778/1453856.1453943     Document Type: Article

References (54)

1. S. Abiteboul, R. Hull, and V. Vianu. Foundations of Databases. Addison Wesley Publishing Co, 1995.
2. Amazon.com: http://www.amazon.com/.
3. R. Ananthakrishna, S. Chaudhuri, and V. Ganti. Eliminating fuzzy duplicates in data warehouses. In VLDB, pages 586-597, 2002.
4. S. Babu, M. Garofalakis, and R. Rastogi. Spartan: A model-based semantic compression system for massive data tables. In SIGMOD, pages 283-294, 2001.
5. P. Beame. A switching lemma primer. Technical Report 95-07-01, University of Washington, Seattle, WA, 1995.
6. O. Benjelloun, A. Das Sarma, A. Y. Halevy, M. Theobald, and J. Widom. Databases with uncertainty and lineage. VLDB J., 17(2):243-264, 2008.
7. O. Benjelloun, A. Das Sarma, C. Hayworth, and J. Widom. An introduction to ULDBs and the Trio system. IEEE Data Eng. Bull, 29(1):5-16, 2006.
8. A. Blum, M. L. Furst, J C. Jackson, M J. Kearns, Y. Mansour, and S. Rudich. Weakly learning dnf and characterizing statistical query learning using fourier analysis. In STOC, pages 253-262, 1994.
9. B. Boeckmann, A. Bairoch, R. Apweiler, M. C. Blatter, A. Estreicher, E. Gasteiger, M. J. Martin, K. Michoud, C. O'Donovan, I. Phan, S. Pilbout, and M. Schneider. The swiss-prot protein knowledgebase and its supplement trembl in 2003. Nucleic Acids Res, 31(1):365-370, January 2003.
10. J. Boulos, N.Dalvi, B. Mandhani, S. Mathur, C. Re, and D. Suciu. Mystiq: A system for finding more answers using probabilities (demo). In SIGMOD, 2005.
11. N. Bshouty and C. Tamon. On the fourier spectrum of monotone functions. J. ACM, 43(4):747-770, 1996.
12. P. Buneman, A. Chapman, and J. Cheney. Provenance management in curated databases. In SIGMOD, pages 539-550, 2006.
13. A. Chapman and H. V. Jagadish. Issues in building practical provenance systems. IEEE Data Eng. Bull., 30(4):38-43, 2007.
14. The Gene Ontology Consortium. Gene ontology: tool for the unification of biology. In Nature Genet., pages 25-29, (2000).
15. R. G. Cowell, S. L. Lauritzen, A. P. David, and D. J. Spiegelhalter. Probabilistic Networks and Expert Systems. Springer-Verlag New York, Inc., Secaucus, NJ, USA, 1999.
16. N. Dalvi and D. Suciu. Efficient query evaluation on probabilistic databases. In VLDB, Toronto, Canada, 2004.
17. Special issue on data provenance. IEEE Data Eng. Bull., 30(4), 2007.
18. A. Deligiannakis, M. Garofalakis, and N. Roussopoulos. Extended wavelets for multiple measures. ACM Trans. Database Syst., 32(2):10, 2007.
19. M. Eltabakh, M. Ouzzani, and W. G. Aref. bdbms - a database management system for biological data. In CIDR, pages 196-206, 2007.
20. R. Fagin, J. Y. Halpern, and N. Megiddo. A logic for reasoning about probabilities. Information and Computation, 87(1/2):78-128, 1990.
21. http://flybase.bio.indiana.edu/.
22. N. Fuhr and T. Roelleke. A probabilistic relational algebra for the integration of information retrieval and database systems. ACM Trans. Inf. Syst., 15(1):32-66, 1997.
23. M. Garofalakis and P. Gibbons. Probabilistic wavelet synopses. ACM Trans. Database Syst., 29:43-90, 2004.
24. L. Getoor, B. Taskar, and D. Koller. Selectivity estimation using probabilistic models. In SIGMOD, pages 461-472, 2001.
25. J. Goldstein, R. Ramakrishnan, and U. Shaft. Compressing relations and indexes. In ICDE, pages 370-379, 1998.
26. S.M. Gorski, S. Chittaranjan, E.D. Pleasance, J.D. Freeman, C.L. Anderson, R.J. Varhol, S.M. Coughlin, S.D. Zuyderduyn, S.J. Jones, and M.A. Marra. A SAGE approach to discovery of genes involved in autophagic cell death. Curr. Biol., 13:358-363, Feb 2003.
27. E. Gr̈adel, Y. Gurevich, and C. Hirsch. The complexity of query reliability. In PODS, pages 227-234, 1998.
28. T. Green, G. Karvounarakis, N. E. Taylor, O. Biton, Z. G. Ives, and V. Tannen. Orchestra: facilitating collaborative data sharing. In SIGMOD, pages 1131-1133, 2007.
29. T. Green and V. Tannen. Models for incomplete and probabilistic information. IEEE Data Engineering Bulletin, 29(1):17-24, March 2006.
30. T. J. Green, G. Karvounarakis, and V. Tannen. Provenance semirings. In PODS, pages 31-40, 2007.
31. J. Halpern and J. Pearl. Causes and explanations: A structural-model approach -part II: Explanations. In IJCAI, pages 27-34, 2001.
32. J. Håstad. Computational limitations for small depth circuits. M.I.T Press, Cambridge, Massachusetts, 1986.
33. E. Hazan, S. Safra, and O. Schwartz. On the hardness of approximating k-dimensional matching. ECCC, 10(020), 2003.
34. M. Hernandez and S. Stolfo. The merge/purge problem for large databases. In SIGMOD, pages 127-138, 1995.
35. Internet movie database: http://www.imdb.com/.
36. T. Imielinski and W. Lipski. Incomplete information in relational databases. Journal of the ACM, 31:761-791, October 1984.
37. M. Jordan, Z. Ghahramani, T. Jaakkola, and L. Saul. An introduction to variational methods for graphical models. Machine Learning, 37(2):183-233, 1999.
38. R. Karp and M. Luby. Monte-Carlo algorithms for enumeration and reliability problems. In Proceedings of the annual ACM symposium on Theory of computing, 1983.
39. E. Kushilevitz and Y. Mansour. Learning decision trees using the fourier spectrum. SIAM J. Comput., 22(6):1331-1348, 1993.
40. N. Linial, Y. Mansour, and N. Nisan. Constant depth circuits, fourier transform, and learnability. J. ACM, 40(3):607-620, 1993.
41. G. Miklau and D. Suciu. A formal analysis of information disclosure in data exchange. J. Comput. System Sci., 73(3):507-534, 2007.
42. R. Motwani and P. Raghavan. Randomized Algorithms. Cambridge University Press, August 1995.
43. R. W. O'Donnell. Computational Applications of Noise Sensitivity. PhD thesis, M.I.T., 2003.
44. J. Pearl. Causality: Models, Reasoning and Inference. Cambridge University Press, Cambridge, UK, 2000.
45. http://www.pubmed.gov.
46. C. Ré, N. Dalvi, and D. Suciu. Efficient top-k query evaluation on probabilistic data. In ICDE, 2007.
47. C. Ré and D. Suciu. Materialized views in probabilistic databases for information exchange and query optimization. In VLDB, pages 51-62, 2007.
48. N. Segerlind, S. R. Buss, and R. Impagliazzo. A switching lemma for small restrictions and lower bounds for k-dnf resolution. SIAM J. Comput., 33(5):1171-1200, 2004.
49. P. Sen and A. Deshpande. Representing and querying correlated tuples in probabilistic databases. In ICDE, 2007.
50. R. Servedio. On learning monotone dnf under product distributions. Inf. Comput., 193(1):57-74, 2004.
51. M. Stonebraker, D. Abadi, A. Batkin, X. Chen, M. Cherniack, M. Ferreira, E. Lau, A. Lin, S. Madden, E. O'Neil, P. O'Neil, A. Rasin, N. Tran, and S. Zdonik. C-store: A column-oriented dbms. In VLDB, pages 553-564, 2005.
52. Go database v. go200801.
53. J. Vitter and M. Wang. Approximate computation of multidimensional aggregates of sparse data using wavelets. In SIGMOD, pages 193-204, 1999.
54. J. Widom. Trio: A system for integrated management of data, accuracy, and lineage. In CIDR, pages 262-276, 2005.