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Combining decidability paradigms for existential rules

Published online by Cambridge University Press:  25 September 2013

GEORG GOTTLOB ,
MARCO MANNA  and
ANDREAS PIERIS
GEORG GOTTLOB
Affiliation:
Department of Computer Science, University of Oxford, UK (e-mail: georg.gottlob@cs.ox.ac.uk)
MARCO MANNA
Affiliation:
Department of Mathematics and Informatics, University of Calabria, Italy (e-mail: manna@mat.unical.it)
ANDREAS PIERIS
Affiliation:
Department of Computer Science, University of Oxford, UK (e-mail: andreas.pieris@cs.ox.ac.uk)
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Abstract

Existential rules are Datalog rules extended with existential quantifiers in rule-heads. Three fundamental restriction paradigms that have been studied for ensuring decidability of query answering under existential rules are weak-acyclicity, guardedness and stickiness. Towards the identification of even more expressive decidable languages, several attempts have been conducted to consolidate weak-acyclicity with the other two paradigms. However, it is not clear how guardedness and stickiness can be merged; this is the subject of this paper. A powerful and flexible condition, called tameness, is proposed, which allows us to consolidate in an elegant and uniform way guardedness with stickiness.

Keywords

datalog extensionsquery answeringdecidabilitycomplexityguardednessstickiness

Information

Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 13 , Special Issue 4-5: 29th International Conference on Logic Programming , July 2013 , pp. 877 - 892
Copyright
Copyright © 2013 [GEORG GOTTLOB, MARCO MANNA and ANDREAS PIERIS] 

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References

Alviano, M., Faber, W., Leone, N. and Manna, M. 2012. Disjunctive datalog with existential quantifiers: Semantics, decidability, and complexity issues. Theory and Practice of Logic Programming 12, 4–5, 701–718.CrossRefGoogle Scholar
Andréka, H., van Benthem, J. and Németi, I. 1998. Modal languages and bounded fragments of predicate logic. Journal of Philosophical Logic 27, 217–274.CrossRefGoogle Scholar
Baget, J.-F., Leclère, M., Mugnier, M.-L. and Salvat, E. 2011. On rules with existential variables: Walking the decidability line. Artificial Intelligence 175, 9–10, 1620–1654.CrossRefGoogle Scholar
Barany, V., Gottlob, G. and Otto, M. 2010. Querying the guarded fragment. In Proceedings of the 25th IEEE Symposium on Logic in Computer Science, 1–10.Google Scholar
Beeri, C. and Vardi, M. Y. 1981. The implication problem for data dependencies. In Proceedings of the 8th International Colloquium on Automata, Languages and Programming, 73–85.Google Scholar
Bourhis, P., Morak, M. and Pieris, A. 2013. The impact of disjunction on query answering under guarded-based existential rules. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence, To appear.Google Scholar
Calì, A., Gottlob, G. and Kifer, M. 2008. Taming the infinite chase: Query answering under expressive relational constraints. In Proceedings of the 11th International Conference on Principles of Knowledge Representation and Reasoning, 70–80.Google Scholar
Calì, A., Gottlob, G. and Lukasiewicz, T. 2012. A general Datalog-based framework for tractable query answering over ontologies. Journal of Web Semantics 14, 57–83.CrossRefGoogle Scholar
Calì, A., Gottlob, G. and Pieris, A. 2012. Towards more expressive ontology languages: The query answering problem. Artificial Intelligence 193, 87–128.CrossRefGoogle Scholar
Ceri, S., Gottlob, G. and Tanca, L. 1990. Logic Programming and Databases. Springer.CrossRefGoogle Scholar
Chandra, A. K. and Merlin, P. M. 1977. Optimal implementation of conjunctive queries in relational data bases. In Proceedings of the 9th Annual ACM Symposium on Theory of Computing, 77–90.CrossRefGoogle Scholar
Deutsch, A., Nash, A. and Remmel, J. B. 2008. The chase revisisted. In Proceedings of the 27th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, 149–158.Google Scholar
Fagin, R., Kolaitis, P. G., Miller, R. J. and Popa, L. 2005. Data exchange: Semantics and query answering. Theoretical Computer Science 336, 1, 89–124.CrossRefGoogle Scholar
Gebser, M., Kaufmann, B., Neumann, A. and Schaub, T. 2007. Conflict-driven answer set solving. In Proceedings of the 20th International Joint Conference on Artificial Intelligence, 386–392.Google Scholar
Gogacz, T. and Marcinkowski, J. 2013. Converging to the chase - a tool for finite controllability. In Proceedings of the 28th Annual IEEE Symposium on Logic in Computer Science, To appear.CrossRefGoogle Scholar
Gottlob, G. and Koch, C. 2004. Monadic Datalog and the expressive power of languages for web information extraction. Journal of the ACM 51, 1, 74–113.CrossRefGoogle Scholar
Gottlob, G., Manna, M., Morak, M. and Pieris, A. 2012. On the complexity of ontological reasoning under disjunctive existential rules. In Proceedings of the 37th International Symposium Mathematical Foundations of Computer Science, 1–18.Google Scholar
Hajiyev, E., Verbaere, M. and de Moor, O. 2006. codeQuest: Scalable source code queries with Datalog. In Proceedings of the 20th European Conference on Object-Oriented Programming, 2–27.Google Scholar
Johnson, D. S. and Klug, A. C. 1984. Testing containment of conjunctive queries under functional and inclusion dependencies. Journal of Computer and System Sciences 28, 1, 167–189.CrossRefGoogle Scholar
Krötzsch, M. and Rudolph, S. 2011. Extending decidable existential rules by joining acyclicity and guardedness. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence, 963–968.Google Scholar
Leone, N., Manna, M., Terracina, G. and Veltri, P. 2012. Efficiently computable Datalog∃ programs. In Proceedings of the 13th International Conference on Principles of Knowledge Representation and Reasoning.Google Scholar
Leone, N., Pfeifer, G., Faber, W., Eiter, T., Gottlob, G., Perri, S. and Scarcello, F. 2006. The DLV system for knowledge representation and reasoning. ACM Transactions on Computational Logic 7, 3, 499–562.CrossRefGoogle Scholar
Lierler, Y. and Maratea, M. 2004. Cmodels-2: SAT-based answer set solver enhanced to non-tight programs. In Proceedings of the 7th International Conference on Logic Programming and Nonmonotonic Reasoning, 346–350.Google Scholar
Maier, D., Mendelzon, A. O. and Sagiv, Y. 1979. Testing implications of data dependencies. ACM Transactions on Database Systems 4, 4, 455–469.CrossRefGoogle Scholar
Marczak, W. R., Alvaro, P., Conway, N., Hellerstein, J. M. and Maier, D. 2012. Confluence analysis for distributed programs: A model-theoretic approach. In Proceedings of Datalog 2.0. 135–147.CrossRefGoogle Scholar
Patel-Schneider, P. F. and Horrocks, I. 2007. A comparison of two modelling paradigms in the semantic web. Journal of Web Semantics 5, 4, 240–250.CrossRefGoogle Scholar
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