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Abductive Conjunctive Query Answering w.r.t. Ontologies

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Abstract

In this article we investigate abductive conjunctive query answering w.r.t. ontologies and show how use cases can benefit from this kind of query answering service. While practical reasoning systems such as Racer have supported abductive conjunctive query answering for 10 years now, and many projects have exploited this feature, few publications deal with A-box abduction from an implementation perspective. This article gives a generalized overview on features provided by practical systems and also explains optimization techniques needed to meet practical requirements.

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Notes

  1. A slightly different approach for ranking different interpretation possibilities based on probabilistic logic is presented in [22].

References

  1. Kakas A, Kowalski R, Toni F (1993) Abductive logic programming. J Logic Comput 2(6):239–770

    MathSciNet  MATH  Google Scholar 

  2. Gaasterland T, Godfrey P, Minker J (1992) Relaxation as a platform for cooperative answering. J Intell Inf Syst 1:293–321

    Article  Google Scholar 

  3. Shanahan M (2005) Perception as abduction: turning sensor data into meaningful representation. Cognit Sci 29(1):103–134

    Article  MathSciNet  Google Scholar 

  4. Petasis G, Möller R, Karkaletsis V (2013) Boemie: reasoning-based information extraction. In: Proceedings of the 1st workshop on natural language processing and automated reasoning co-located with 12th international conference on logic programming and nonmonotonic reasoning (LPNMR 2013), pp 60–75

  5. Haarslev V, Hidde K, Möller R, Wessel M (2012) The RacerPro knowledge representation and reasoning system. Seman Web J 3(3):267–277

    Google Scholar 

  6. Espinosa S, Kaya A, Möller R (2009) The BOEMIE semantic browser: a semantic application exploiting rich semantic metadata. In: Proceedings of the applications of semantic technologies workshop (AST-2009), Lübeck, Germany

  7. Lenat DB, Feigenbaum EA (1991) On the thresholds of knowledge. Artif Intell 47(1–3):185–250

    Article  MathSciNet  Google Scholar 

  8. Denecker M, Kakas AC (2002) Abduction in logic programming. In: Kakas AC, Sadri F (eds) Computational logic: logic programming and beyond, essays in honour of Robert A. Kowalski, part I. Lecture notes in computer science, vol 2407. Springer, Berlin, pp 402–436

  9. Möller R, Neumann B (2008) Ontology-based reasoning techniques for multimedia interpretation and retrieval. In: Semantic multimedia and ontologies : theory and applications. Springer, Berlin, pp 55–98

  10. Espinosa Peraldi S, Kaya A, Melzer S, Möller R (2008) On ontology based abduction for text interpretation. In: Gelbukh A (ed) Proceedings of 9th international conference on intelligent text processing and computational linguistics (CICLing-2008)

  11. Dolog P, Stuckenschmidt H, Wache H, Diederich J (2009) Relaxing rdf queries based on user and domain preferences. J Intell Inf Syst 33:239–260

    Article  Google Scholar 

  12. Espinosa S (2011) Content management and knowledge management: two faces of ontology-based text interpretation. PhD thesis, Hamburg University of Technology

  13. Espinosa S, Atila K, Möller R (2011) Knowledge-driven multimedia information extraction and ontology evolution. In: LNCS, chapter logical formalization of multimedia interpretation, vol 6050. Springer, Berlin, pp 110–133

  14. Kaya A (2010) A logic-based approach to multimedia interpretation. PhD thesis, Hamburg University of Technology

  15. Castano S, Peraldi ISE, Ferrara A, Karkaletsis V, Kaya A, Möller R, Montanelli S, Petasis G, Wessel M (2009) Multimedia interpretation for dynamic ontology evolution. J. Log. Comput. 19(5):859–897

    Article  MathSciNet  MATH  Google Scholar 

  16. Espinosa S, Kaya A, Möller R (2009) Formalizing multimedia interpretation based on abduction over description logic aboxes. In: Proceedings of the 2009 international workshop on description logics DL- 2009, 27 to 30 July 2009. CEUR workshop proceedings, vol 477, Oxford, UK

  17. Du J, Guilin Q, Yi-Dong S, Jeff PZ (2012) Towards practical abox abduction in large description logic ontologies. Int. J. Seman. Web Inf. Syst. 8(2):1–33

    Article  Google Scholar 

  18. Klarman S, Endriss U, Schlobach S (2011) Abox abduction in the description logic ALC. J Autom Reas 46(1):43–80

    Article  MathSciNet  MATH  Google Scholar 

  19. Ma Y, Gu T, Xu B, Chang L (2012) An abox abduction algorithm for the description logic alci. In: Intelligent information processing VI. IFIP advances in information and communication technology, vol 385. Springer, Berlin, pp 125–130

  20. Hobbs JR, Stickel ME, Appelt DE, Martin PA (1993) Interpretation as abduction. Artif Intell 63(1–2):69–142

    Article  Google Scholar 

  21. Gries O, Möller R, Nafissi A, Rosenfeld M, Sokolski K, Wessel M (2010) A probabilistic abduction engine for media interpretation based on ontologies. In: Hitzler P, Lukasiewicz T (eds) Web reasoning and rule systems—fourth international conference, RR 2010, Bressanone/Brixen, Italy, September 22–24, 2010. Proceedings. Lecture notes in computer science, vol 6333. Springer, Berlin, pp 182–194

  22. Nafissi A (2013) Applying markov logics for controlling abox abduction. PhD thesis, Hamburg University of Technology

  23. Baader F, Peñaloza R (2010) Axiom pinpointing in general tableaux. J Logic Comput 20(1):5–34 (Special Issue: Tableaux and Analytic Proof Methods)

    Article  MathSciNet  MATH  Google Scholar 

  24. Kalyanpur A, Parsia B, Horridge M, Sirin E (2007) Finding all justifications of owl dl entailments. In: The semantic web. Springer, Berlin, pp 267–280

  25. Özçep OL, Möller R, Neuenstadt C (2014) A stream-temporal query language for ontology based data access. In: KI 2014, vol 8736. LNCS, pp 183–194

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Correspondence to Ralf Möller.

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Möller, R., Özçep, Ö., Haarslev, V. et al. Abductive Conjunctive Query Answering w.r.t. Ontologies. Künstl Intell 30, 177–182 (2016). https://doi.org/10.1007/s13218-015-0399-3

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