Abstract
Deductive database systems have made major advances on efficient support for nonmonotonic reasoning. A first generation of deductive database systems supported the notion of stratification for programs with negation and set aggregates. Stratification is simple to understand and efficient to implement but it is too restrictive; therefore, a second generation of systems seeks efficient support for more powerful semantics based on notions such as well-founded models and stable models. In this respect, a particularly powerful set of constructs is provided by the recently enhanced LDL++ system that supports (i) monotonie user-defined aggregates, (ii) XY-stratified programs, and (iii) the nondeterministic choice constructs under stable model semantics. This integrated set of primitives supports a terse formulation and efficient implementation for complex computations, such as greedy algorithms and data mining functions, yielding levels of expressive power unmatched by other deductive database systems.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Abiteboul, S., Hull, R. and Vianu, V. (1995). Foundations of Databases. Addison-Wesley, Reading, MA, 1995.
Baudinet, M., Chomicki, J., and Wolper, P. (1994). Temporal Deductive Databases, Chapter 13 of Temporal Databases: Theory, Design, and Implementation, A. Tansel et al. (eds), pp. 294–320, Benjamin/Cummings, 1994.
Brogi, A, Subrahmanian, V. S. and Zaniolo, C. (1997). The Logic of Totally and Partially Ordered Plans: A Deductive Database Approach, Annals of Mathematics and Artificial Intelligence 19(1–2): 27–58 (1997).
Eiter, T. et al. (2000). Declarative Problem-Solving Using the DLV System, In Minker, J., editor, Logic-Based Artificial Intelligence, pages 79–103, Kluwer Academic Publishers, Norwell, Massachusetts, 02061.
Bonchi, F. et al. (1999). “Applications of LDL++ to Datamining: A Classification-Based Methodology for Planning Audit Strategies in Fraud Detection”, Proc. Fifth ACM SIGKDD Int. Conference on Knowledge Discovery and Data Mining, KDD’99 175–184, ACM, 1999.
Chimenti, D. et al. (1990). The LDL System Prototype. IEEE Transactions on Knowledge and Data Engineering, 2(1), 76–90 (1990).
Finkelstein, S. J., et al.(1996) Expressing Recursive Queries in SQL, ISO WG3 report X3H2-96-075, March 1966.
Hellerstein, J. M., Haas, P.J. and Wang, H.J. (1997). “Online Aggregation”. Proc. ACM SIGMOD Int. Conference on Management of Data, 171–182, ACM, 1997.
Ganguly, S., Greco, S. and Zaniolo, C. (1995). “Extrema Predicates in Deductive Databases,” JCSS 51(2): 244–259 (1995)
Gelfond, M. and Lifschitz, V. (1988). The Stable Model Semantics for Logic Programming. Proc. Joint International Conference and Symposium on Logic Programming, R. A. Kowalski and K. A. Bowen, eds., pp. 1070–1080, MIT Press, 1988.
Giannotti, F. et al. (1981). Non-Determinism in Deductive Databases. DOOD’91, C. Delobel, M. Kifer, Y. Masunaga (Eds.), pp. 129–146, Springer, 1991.
Giannotti, F., et al. (1999). On the Effective Semantics of Nondeterministic, Nonmonotonic, Temporal Logic Databases, Proc. 12th Int. Workshop, Computer Science Logic, pp. 58–72, LNCS Vol. 1584, Springer, 1999.
Giannotti, F., Pedreschi, D. and Zaniolo, C. (2000). “Semantics and Expressive Power of Non-Deterministic Constructs in Deductive Databases,” Journal of Computer and System Sciences, to appear.
Greco, S. and Zaniolo, C. (1998). Greedy Algorithms in Datalog with Choice and Negation, Proc. 1998 Joint Int. Conference & Symposium on Logic Programming, JCSLP’98, pp. 294–309, MIT Press, 1998.
Kemp, D., Ramamohanarao, K., and Stuckey, P. (1995). ELS Programs and the Efficient Evaluation of Non-Stratified Programs by Transformation to ELS. In Proc. Int. Conf on Deductive and Object-Oriented Databases: DOOD’95, T. W. Ling, A. O. Mendelzon, L. Vieille (Eds.): pp. 91–108, Springer, 1995.
Kemp, D. and Ramamohanarao, K. (1998). Efficient Recursive Aggregation and Negation in Deductive Databases. TKDE 10(5): 727–745 (1998).
Krishnamurthy, R., Naqvi, S. (1988) Non-Deterministic Choice in Datalog. Proc. 3nd Int. Conf. on Data and Knowledge Bases, pp. 416–424, Morgan Kaufmann, Los Altos (1988).
Minker, J. (1996). Logic and Databases: A 20 Year Retrospective. Proc. International Workshop on Logic in Databases (LID’96), D. Pedreschi and C. Zaniolo (eds.), pp. 5–52, Springer-Verlag, 1966.
Przymusinski, T.C. (1998). On the Declarative and Procedural Semantics of Stratified Deductive Databases. In J. Minker (ed.), Foundations of Deductive Databases and Logic Programming, pp. 193–216, Morgan Kaufman, San Francisco, CA, 1988.
Lausen, G., Ludaescher, B. and May, W. (1998). On Logical Foundations of Active Databases, In Logics for Databases and Information Systems, J. Chomicki and G. Saake (Eds.), pp. 389–422 Kluwer Academic Publishers, pp. 375–398, 1998.
Rao, P., et al. (1997). XSB: A System for Efficiently Computing WFS. Proc. Fourth Int. Conference on Logic Programming and Non-Monotonic Reasoning, LPNMR’97, J. Dix, U. Furbach, A. Nerode (Eds.), pp. 431–441, Springer 1997
Ramakrishnan, R., et al. (1993). Implementation of the CORAL Deductive Database System. Proc. International ACM SIGMOD Conference on Management of Data, pp. 167–176, 1993.
Ramakrishnan, R., and Ullman J.D. (1995). A survey of deductive database systems. LLP, 23(2): 125–149 (1995)
Ross, K.A. (1994). Modular Stratification and Magic Sets for Datalog Programs with Negation. Journal of ACM 41(6):1216–1266, 1994.
Ross, K.A. and Sagiv, Y. (1997). “Monotonie Aggregation in Deductive Database”, JCSS, 54(1), 79–97 (1997).
Shen, W., et al. (1996). Metaqueries for Data Mining, Chapter 15 of Advances in Knowledge Discovery and Data Mining, U. M. Fayyad et al (eds.), pp. 201–217, MIT Press, 1996.
Schlipf, J.S. (1992). A Survey of Complexity and Undecidability Results in Logic Programming, Proc. Workshop on Structural Complexity and Recursion-Theoretic Methods in Logic Programming, 1993, pp. 143–164
Vaghani, J., et al. (1994) The Aditi Deductive Database System. The VLDB Journal, 3(2), pp. 245–288 (1994).
Van Gelder, A., Ross, K.A. and Schlipf, J.S. (1990). The Well-Founded Semantics for General Logic Programs. Journal of ACM 38:620–650, 1991.
Van Gelder, A. (1990). Foundations of Aggregations in Deductive Databases Proc. of Int. Conf. On Deductive and Object-Oriented databases, DOOD’93, S. Ceri, K. Tanaka, S. Tsur (Eds.), pp. 13–34, Springer, 1993.
Tsur, S. (1991). Deductive Databases in Action, Proc. ACM SIGACT- SIGMOD-SIGART Symposium on Principles of Programming Languages, pp. 142–154, 1991.
Zaniolo, C, Arni, N. Ong, K. (1993). Negation and Aggregates in Recursive Rules: the LDL++ Approach. DOOD’93, S. Ceri, K. Tanaka, S. Tsur (Eds.), pp. 204–221, Springer, 1993.
Wang, H. and Zaniolo, C. (2000). User-Defined Aggregates in Object-Relational Database Systems. International Conference on Database Engineering, pp. 111–121, IEEE Press, 2000.
Zaniolo, C. and Wang, H. (1999). Logic-Based User-Defined Aggregates for the Next Generation of Database Systems. In The Logic Programming Paradigm: Current Trends and Future Directions. K.R. Apt, V. Marek, M. Truszczynski, D.S. Warren (eds.), Springer Verlag, pp. 401–424, 1999.
Zaniolo, et al. (1997) Advanced Database Systems, Morgan Kaufmann Publishers, 1997.
Zaniolo, C. (1997). The Nonmonotonic Semantics of Active Rules in Deductive Databases. DOOD 1997, F. Bry, R. Ramakrishnan, K. Ramamohanarao (Eds.) pp. 265–282, Springer, 1997.
Zaniolo, C. et al. (1998) LDL++ Documentation and Web Demo, 1988: http://www.cs.ucla.edu/ldl
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer Science+Business Media New York
About this chapter
Cite this chapter
Wang, H., Zaniolo, C. (2000). Nonmonotonic Reasoning in LDL++ . In: Minker, J. (eds) Logic-Based Artificial Intelligence. The Springer International Series in Engineering and Computer Science, vol 597. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-1567-8_22
Download citation
DOI: https://doi.org/10.1007/978-1-4615-1567-8_22
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-5618-9
Online ISBN: 978-1-4615-1567-8
eBook Packages: Springer Book Archive