Query evaluation in probabilistic relational databases

Theoretical Computer Science

Volumn 171, Issue 1-2, 1997, Pages 179-219

  Zimányi, Esteban ^a  

^a UNIVERSITÉ LIBRE DE BRUXELLES   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMIC LANGUAGES; DATABASE SYSTEMS; LOGIC PROGRAMMING; PROBABILITY;

PROBABILISTIC INFORMATION; PROBABILISTIC RELATIONAL DATABASES;

PROBABILISTIC LOGICS;

EID: 0030736377     PISSN: 03043975     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0304-3975(96)00129-6     Document Type: Article

References (43)

1. D. Barbará, H. García-Molína and D. Porter, A probabilistic relational data model, in: F. Bancilhon, C. Thanos and D. Tsichrítzis, eds., Proc. Internat. Conf. on Extending Database Technology, EDBT'90 (Venice, Italy, 1990) Lecture Notes in Computer Science, Vol. 416 (Springer, Berlin, 1990) 60-74.
2. R. Cavallo and M. Pittarelli, The theory of probabilistic database, in: Proc. 13th Internet. Conf. on Very Large Databases (Brighton, U.K., 1987).
3. E. Codd, Extending the database relational model to capture more meaning, ACM Trans. on Database Systems 4(4) (1979) 397-434.
4. R. Elmasri and S. Navathe, Fundamentals of Database Systems. (Benjamin/Cummings, Menlo Park, CA, 2 ed., 1994).
5. R. Fagin, J. Halpern and N. Meggido, A logic for reasoning about probabilities, Inform. and Comput., 87 (1990) 78-128.
6. E. Gelenbe and G. Hebrail, A probability model of uncertainty in databases, in: Proc. Internat. Conf. on Data Engineering (1986).
7. G. Grahne, The Problem of Incomplete Information in Relational Databases, Lecture Notes in Computer Science, Vol. 554. (Springer, Berlin, 1991).
8. U. Güntzer, W. Kießling, and H. Thöne, New directions for uncertainty reasoning in deductive databases, in: Proc. ACM-SIGMOD Internat. Conf. on Management of Data, (Denver, 1991) 178-187.
9. J. Halpern, An analysis of first-order logics of probability, Artificial Intell. 46(3) (1990) 311-350.
10. G. Hulin, A. Pirotte, D. Roelants and M. Vauclair, Logic and databases, in: A. Thayse, ed., From Modal Logic to Deductive Databases (Wiley, New York, 1989) 279-350.
11. T. Imieliński and W. Lipski, Jr., Incomplete information in relational databases, J. ACM 31(4) (1984) 761-791.
12. T. Imielinski and K. Vadaparty, Complexity of query processing in databases with or-objects, in: Proc. 8th ACM SIGACT-SIGMOD Symp. on Principles of Database Systems (1989).
13. W. Kießling, H. Thöne and U. Güntzer, Database support for problematic knowledge, in: A. Pirotte, C. Delobel and G. Gottlob, eds., Proc. Internet. Conf. on Extending Database Technology, EDBT'92 (Vienna, Austria, 1992) (Springer, Berlin, 1992).
14. M. Lacroix and A. Pirotte, Generalized joins, ACM SIGMOD Record 8(3) (1976).
15. V. Lakshmanan, An epistemic foundation for logic programming with uncertainty, in: Proc. Internet. Conf. on Foundations of Software Technology and Theoretical Computer Science, Lecture Notes in Computer Science, Vol. 880 (Madras, India, 1994) (Springer, Berlin, 1994) 197-207.
16. V. Lakshmanan and F. Sadri, Modeling uncertainty in deductive databases, in: Proc. Internat. Conf. on Database Expert Systems and Applications, DEXA'94 (Athens, Greece, 1994), Lecture Notes in Computer Science, Vol. 856 (Springer, Berlin, 1994) 197-207.
17. V. Lakshmanan and F. Sadri, Probabilistic deductive databases, in: Proc. Internat. Logic Programming Symp., (Ithaca, NY, Nov. 1994) (MIT Press, Cambridge, MA, 1994) 197-207.
18. K. Liu and R. Sunderraman, Indefinite and maybe information in relational databases, ACM Trans. on Database Systems 15(1) (1990) 1-39.
19. K. Liu and R. Sunderraman, A generalized relational model for indefinite and maybe information, IEEE Trans. on Knowledge and Data Engineering 3(1) (1991) 65-77.
20. R. Miller, Switching Theory, vol. 1: Combinatorial Circuits (Wiley, New York, 1965).
21. J. Minker, On indefinite databases and the closed world assumption, in: D.W. Loveland, ed., Proc. 6th Conf. on Automated Deduction (New York, USA, June 1982) Lecture Notes in Computer Science, Vol. 138 (Springer, Berlin, 1982) 292-308.
22. J. Minker, Toward a foundation of disjunctive logic programming, in: E. Lusk and R. Overbeek, eds., Proc. North American Logic Programming Conf. (MIT Press, Cambridge, MA, 1989) 1215-1235.
23. R. Ng and V. Subrahmanian, Probabilistic logic programming, Inform. and Comput. 101(2) (1992) 150-201.
24. R. Ng and V. Subrahmanian, A semantical framework for supporting subjective and conditional probabilities in deductive databases, J. Autom. Reasoning 10(2) (1993) 191-235.
25. R. Ng and V. Subrahmanian, Stable semantics for probabilistic databases, Inform. and Comput. 110(1) (1994) 42-83.
26. M. Pittarelli, An algebra for probabilistic databases, IEEE Trans. on Knowledge and Data Eng. 6(2) (1994) 293-303.
27. A. Rajasekar, J. Lobo and J. Minker, Weak generalized closed world assumption, J. Autom. Reasoning 5(3) (1989) 293-307.
28. K. Raju and A.K. Majumdar, Fuzzy functional dependencies and lossless join decomposition of fuzzy relational database systems, ACM Trans. on Database Systems 13(2) (1988) 129-166.
29. R. Reiter, Towards a logical reconstruction of relational database theory, in: M. Brodie, J. Mylopoulos and J. Schmidt, eds., On Conceptual Modelling (Springer, Berlin, 1984) 191-238.
30. R. Reiter, A sound and sometimes complete query evaluation algorithm for relational databases with null values, J. ACM, 33(2) (1986) 349-370.
31. R. Reiter and J. de Kleer, Foundations of assumption-based truth maintenance system: Preliminary report, in: Proc. AAAI-87 (1987) 183-188.
32. K. Ross and R. Topor, Inferring negative information from disjunctive databases, J. Autom. Reasoning 4 (1988) 397-424.
33. F. Sadri, Modeling uncertainty in databases, in: Proc. 7th IEEE Internat. Conf. on Data Eng. (1991) 122-131.
34. F. Sadri, Reliability of answers to queries in relational databases, IEEE Trans, on Knowledge and Data Eng. 3(2) (1991) 245-251.
35. J. Shoenfield, Mathematical Logic (Addison-Wesley, Massachusetts, 1967).
36. L. Sombe, Reasoning under Uncertain Information in Artificial Intelligence (Wiley, New York, 1990).
37. A. Van Gelder and R. Topor, Safety and translation of relational calculus queries, ACM Trans. on Database Systems 16(2) (1991) 235-278.
38. L. Yuan and D.-A. Chiang, A sound and complete query evaluation algorithm for relational databases with null values, in: Proc. ACM-SIGMOD Internat. Conf. on Management of Data (Chicago, 1988) 74-81.
39. L. Zadeh, Fuzzy sets, Inform. and Control 8 (1965) 338-353.
40. L. Zadeh, Fuzzy sets as a basis for theory of possibility, Fuzzy Sets Systems, 1(1) (1978) 3-28.
41. L. Zadeh, A thery of approximate reasoning, in: J.H. et al., eds., Machine Intelligence 9 (Ellis Hoorwood Ltd., Sussex, UK, 1985) 149-194.
42. E. Zimányi, Incomplete and Uncertain Information in Relational Databases, Ph.D. thesis, Université Libre de Bruxelles, Belgium (1992).
43. E. Zimányi and A. Pirotte, Imperfect knowledge in databases, in: A. Motro and P. Smets, eds., Uncertainty Management in Information Systems: from Needs to Solutions (Kluwer, Dordrecht, 1996) in press; Long version in Research Report RR 92-36, Unité d'Informatique, Faculté des Sciences Appliquées, UCL.