Coping with inconsistent constraint specifications

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2224, Issue , 2001, Pages 241-255

  Hartmann, Sven ^a  

^a UNIVERSITY OF ROSTOCK   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SCIENCE; COMPUTERS;

CARDINALITY CONSTRAINTS; CONFLICT RESOLUTION; CONSISTENCY CHECKING; CONSTRAINT SPECIFICATIONS; DATABASE APPLICATIONS; ENTITY-RELATIONSHIP MODELING; INTEGRITY CONSTRAINTS; SEMANTIC INFORMATION;

SEMANTICS;

EID: 84941150121     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45581-7_19     Document Type: Conference Paper

References (24)

1. M. Albrecht, E. Buchholz, A. Düsterhöft, and B. Thalheim. An informal and efficient approach for obtaining semantic constraints using sample data and natural language processing. LNCS, 1358:1–11, 1996.
2. D. Calvanese and M. Lenzerini. On the interaction between ISA and cardinality constraints. In Proc. of Tenth Int. Conf. on Data Engin., pp. 204–213, 1994.
3. P.P. Chen. The entity-relationship model: towards a unified view of data. ACM Trans. Database Syst., 1:9–36, 1976.
4. B.V. Cherkassy and A.V. Goldberg. Negative cycle detection algorithms. Math. Programming, 85:277–311, 1998.
5. B.V. Cherkassy, A.V. Goldberg, and T. Radzik. Shortest path algorithms: theory and experimental evaluation. Math. Programming, 73:129–174, 1996.
6. L. Cholvy and A. Hunter. Information fusion in logic: a brief survey. LNAI, 1244:86–95, 1997.
7. P. Eades, X. Lin, and W.F. Smyth. A fast and effective heuristic for the feedback arc set problem. Inf. Process. Letters, 47:319–323, 1993.
8. M.M. Flood. Exact and heuristic algorithms for the weighted feedback arc set problem. Networks, 20:1–23, 1990.
9. A.V. Goldberg and T. Radzik. A heuristic improvement oft he Bellman-Ford algorithm. Appl. Math. Letters, 6:3–6, 1993.
10. M. Gondran and M. Minoux. Graphs and algorithms. Wiley, Chichecter, 1990.
11. M. Grötchel, M. Jünger, and G. Reichelt. On the acyclic subgraph polytope. Math. Programming, 33:28–42, 1985.
12. S. Hartmann. Graphtheoretic methods to construct entity-relationship databases. LNCS, 1017:131–145, 1995.
13. S. Hartmann. On the consistency ofin t-cardinality constraints. LNCS, 1507:150–163, 1998.
14. S. Hartmann. On interactions ofcard inality constraints, key and functional dependencies. LNCS, 1762:136–155, 2000.
15. S. Hartmann. On the implication problem for cardinality constraints and functional dependencies. Annals Math. Artificial Intell., 2001, to appear.
16. R. Hassin and S. Rubinstein. Approximations for the maximum acyclic subgraph problem. Inf. Process. Letters, 51:133–140, 1994.
17. S.G. Kolliopoulos and C. Stein. Finding real-valued single source shortest paths in o(n3) expected time. In Proc. 5th Int. Prog. Combin. Opt. Conf. 1996.
18. M.L Lee and T.W. Ling. Resolving constraint conflicts in the integration ofen tityrelationship schemas. LNCS, 1331:394–407, 1997.
19. M. Lenzerini and P. Nobili. On the satisfiability ofd ependency constraints in entity-relationship schemata. Inform. Syst., 15:453–461, 1990.
20. S.W. Liddle, D.W. Embley, and S.N. Woodfield. Cardinality constraints in semantic data models. Data Knowledge Eng., 11:235–270, 1993.
21. E. Di Nitto and L. Tanca. Dealing with deviations in DBMSs: an approach to revise consistency constraints. Integrity in Databases, FMLDO96, pp. 11–24. 1996.
22. R.E. Tarjan. Data structures and network algorithms. SIAM, Philadelphia, 1983.
23. B. Thalheim. Entity-relationship modeling. Springer, Berlin, 2000.
24. D. Theodorates. Deductive object oriented schemas. LNCS, 1157:58–72, 1996.