Skip to main content
SpringerLink
Log in

How does incoherence affect inconsistency-tolerant semantics for Datalog±?

  • Published:
Annals of Mathematics and Artificial Intelligence Aims and scope Submit manuscript

Abstract

The concept of incoherence naturally arises in ontological settings, specially when integrating knowledge. In the Datalog± literature, however, this is an issue that is yet to be studied more deeply. The main focus of our work is to show how classical inconsistency-tolerant semantics for query answering behaves when dealing with atoms that are relevant to unsatisfiable sets of existential rules, which may hamper the quality of answers and any reasoning task based on those semantics. We also propose a notion of incoherency-tolerant semantics for query answering in Datalog±, and exemplify this notion with a particular semantics based on the transformation of classic Datalog± ontologies into defeasible Datalog± ones, which use argumentation as its reasoning machinery.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Arenas, M., Bertossi, L.E., Chomicki, J.: Consistent query answers in inconsistent databases. In: Proceedings of PODS, pp 68–79 (1999)

  2. Bell, D.A., Qi, G., Liu, W.: Approaches to inconsistency handling in description-logic based ontologies. In: OTM Workshops, vol. 2, pp 1303–1311 (2007)

  3. Besnard, P., Hunter, A.: Elements of argumentation. MIT Press (2008)

  4. Bienvenu, M.: On the complexity of consistent query answering in the presence of simple ontologies. In: Proceedings of AAAI (2012)

  5. Bienvenu, M., Rosati, R.: Tractable approximations of consistent query answering for robust ontology-based data access. In: Proceedings of IJCAI (2013)

  6. Black, E., Hunter, A., Pan, J.Z.: An argument-based approach to using multiple ontologies. In: SUM, pp 68–79 (2009)

  7. Briguez, C.E., Budȧn, M.C., Deagustini, C.A.D., Maguitman, A.G., Capobianco, M., Simari, G.R.: Argument-based mixed recommenders and their application to movie suggestion. Expert Syst. Appl. 41(14), 6467–6482 (2014)

    Article  Google Scholar 

  8. Calì, A., Gottlob, G., Lukasiewicz, T.: A general Datalog-based framework for tractable query answering over ontologies, vol. 14, pp 57–83 (2012a)

  9. Calì, A., Gottlob, G., Lukasiewicz, T.: A general Datalog-based framework for tractable query answering over ontologies. J. Web Semant. 14, 57–83 (2012b)

    Article  Google Scholar 

  10. Calì, A., Lembo, D., Rosati, R.: On the decidability and complexity of query answering over inconsistent and incomplete databases. In: Proceedings of PODS 2003, pp 260–271. ACM (2003)

  11. Cecchi, L., Fillottrani, P., Simari, G. R.: On the Complexity of Delp through Game Semantics. In: Dix, J., Hunter, A. (eds.) Proceedings 11Th Intl. Workshop on Nonmonotonic Reasoning (NMR 2006, pp 386–394 (2006)

  12. Chomicki, J.: Consistent query answering: five easy pieces. In: Proceedings of ICDT, pp 1–17 (2007)

  13. Croitoru, M., Vesic, S.: What can argumentation do for inconsistent ontology query answering?. In: Scalable uncertainty management, pp 15–29. Springer (2013)

  14. Deagustini, C.A.D., Dalibón, S.E.F., Gottifredi, S., Falappa, M.A., Chesñevar, C.I., Simari, G.R.: Relational databases as a massive information source for defeasible argumentation. Knowl.-Based Syst. 51, 93–109 (2013)

    Article  Google Scholar 

  15. Deagustini, C.A.D., Martinez, M.V., Falappa, M.A., Simari, G.R.: Datalog ± ontology consolidation. J. Artif. Intell. Research (JAIR) (2016). To appear

  16. Delgrande, J.P., Jin, Y.: Parallel belief revision: Revising by sets of formulas. Artif. Intell. 176(1), 2223–2245 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  17. Delgrande, J.P., Schaub, T., Tompits, H.: Stefanwoltran merging logic programs under answer set semantics. In: Hill, P., Warren, D. (eds.) ICLP. Vol. 5649 of lecture notes in computer science, pp 160–174. Springer (2009)

  18. Dung, P.M.: On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artif. Intell. 77, 321–357 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  19. Dunne, P., Wooldridge, M.: Argumentation in artificial intelligence, pp 85–104. Springer, Ch. Complexity of Abstract Argumentation (2009)

  20. Dvoṙák, W., Woltran, S.: Complexity of semi-stable and stage semantics in argumentation frameworks. Inf. Process. Lett. 110(11), 425–430 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  21. Flouris, G., Huang, Z., Pan, J.Z., Plexousakis, D., Wache, H.: Inconsistencies, negations and changes in ontologies. In: AAAI, pp 1295–1300. AAAI Press (2006)

  22. García, A.J., Simari, G.R.: Defeasible logic programming: an argumentative approach. TPLP 4(1–2), 95–138 (2004)

    MathSciNet  MATH  Google Scholar 

  23. Huang, Z., van Harmelen, F., ten Teije, A.: Reasoning with inconsistent ontologies. In: Proceedings of IJCAI, pp 354–359 (2005)

  24. Konieczny, S., Pérez, R.P.: Merging information under constraints: a logical framework. J. Log. Comput. 12(5), 773–808 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  25. Lembo, D., Lenzerini, M., Rosati, R., Ruzzi, M., Savo, D.F.. In: Proceedings of RR, pp 103–117 (2010)

  26. Lukasiewicz, T., Martinez, M.V., Simari, G.I.: Inconsistency handling in Datalog+/– ontologies. In: Proceedings of ECAI, pp 558–563 (2012)

  27. Ma, Y., Hitzler, P.: Paraconsistent reasoning for OWL 2. In: Proceedings of RR. Vol. 5837 of LNCS, pp 197–211. Springer (2009)

  28. Martinez, M.V., Deagustini, C.A.D., Falappa, M.A., Simari, G.R.: Inconsistency-tolerant reasoning in Datalog ± Ontologies via an argumentative semantics. In: Proceedings of IBERAMIA 2014, pp 15–27 (2014)

  29. Martinez, M.V., García, A.J., Simari, G.R.: On the use of presumptions in structured defeasible reasoning. In: Proceedings of COMMA, pp 185–196 (2012)

  30. Prakken, H., Sartor, G.: Argument-based extended logic programming with defeasible priorities. J. Appl. Non-Classical Logics 7(1) (1997)

  31. Qi, G., Du, J.: Model-based revision operators for terminologies in description logics. In: Proceedings of IJCAI, pp 891–897 (2009)

  32. Qi, G., Hunter, A.: Measuring incoherence in description logic-based ontologies. In: ISWC/ASWC, pp 381–394 (2007)

  33. Rahwan, I., Simari, G.R.: Argumentation in artificial intelligence. Springer (2009)

  34. Reiter, R.: A logic for default reasoning. Artif. Intel. 13(1–2), 81–132 (1980)

    Article  MathSciNet  MATH  Google Scholar 

  35. Rosati, R.: On the complexity of dealing with inconsistency in description logic ontologies. In: Proceedings of IJCAI, pp 1057–1062 (2011)

  36. Schlobach, S., Cornet, R.: Non-standard reasoning services for the debugging of description logic terminologies. In: Proceedings of IJCAI 2003, pp 355–362 (2003)

  37. Simari, G.R., Loui, R.P.: A mathematical treatment of defeasible reasoning and its implementation. Artif. Intell. 53(2–3), 125–157 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  38. Thimm, M.: Realizing argumentation in multi-agent systems using defeasible logic programming. In: Argumentation in multi-agent systems, pp 175–194. Springer (2010)

  39. Wooldridge, M., Dunne, P.E., Parsons, S.: On the complexity of linking deductive and abstract argument systems. In: AAAI, vol. 6, pp 299–304 (2006)

Download references

Author information

Authors and Affiliations

  1. AI R&D Lab., Institute for Computer Science and Engineering (ICIC), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional del Sur, Alem 1253, (B8000CPB), Bahía Blanca, Argentina

    Cristhian A. D. Deagustini, M. Vanina Martinez, Marcelo A. Falappa & Guillermo R. Simari

  2. Agents and Intelligent Systems Area, Fac. of Management Sciences, Universidad Nacional de Entre Ríos, (E3202BHR) Concordia, Entre Ríos, Argentina

    Cristhian A. D. Deagustini & Marcelo A. Falappa

Authors
  1. Cristhian A. D. Deagustini
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Vanina Martinez
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marcelo A. Falappa
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Guillermo R. Simari
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Cristhian A. D. Deagustini.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Deagustini, C.A.D., Martinez, M.V., Falappa, M.A. et al. How does incoherence affect inconsistency-tolerant semantics for Datalog±?. Ann Math Artif Intell 82, 43–68 (2018). https://doi.org/10.1007/s10472-016-9519-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10472-016-9519-5

Keywords

Mathematics Subject Classification (2010)

Search

Navigation