Solving Non-deterministic Problem of Ontology Reasoning and Identifying Causes of Inconsistent Ontology using Negated Assumption-based Truth Maintenance System

NATMS를 이용한 온톨로지 추론의 non-deterministic 문제 해결 및 일관성 오류 탐지 기법

  • Published : 2009.05.15

Abstract

In order to derive hidden information (concept subsumption, concept satisfiability and realization) of OWL ontology, a number of OWL reasoners have been introduced. The most of these ontology reasoners were implemented using the tableau algorithm. However most reasoners simply report this information without providing a justification for any arbitrary entailment and unsatisfiable concept derived from OWL ontologies. The purpose of this paper is to investigate an optimized method for non-deterministic rule of the tableau algorithm and finding axioms to cause inconsistency in ontology. In this paper, therefore, we propose an optimized method for non-deterministic rule and finding axiom to cause inconsistency using NATMS. In the first place, we introduce Dependency Directed Backtracking to deal non-deterministic rule, a tableau-based decision procedure to find unsatisfiable axiom Furthermore we propose an improved method adapting NATMS.

온톨로지의 논리적 오류와 개념들 간의 포함 관계를 탐지하는 추론 엔진들이 소개되고 있다. 발표된 온톨로지 추론 엔진의 대부분은 태블로 알고리즘을 기반으로 구축되었다. 그러나 대부분의 추론 엔진들은 논리적 오류를 일으키는 원인은 밝히지 않고, 논리적 오류를 갖는 개념만을 탐지한다. 본 논문의 목적은 태블로 알고리즘 전개 과정 중에 발생하는 non-deterministic 상황을 최적화하는 동시에 논리적 오류를 일으키는 원인을 탐지하기 위한 방법을 연구하는 것이다. 따라서 본 논문에서는 논리적 부정 가정기반 진리 유지 시스템(NATMS)을 사용하여 non-deterministic 문제를 해결하고 논리적 오류 원인을 탐지하는 기법을 제안한다. 본 논문에서는 기존에 발표되었던 종속 부호 기반 백트랙킹 기법과 Swoop 프로젝트에 적용된 논리적 오류 원인을 탐지하는 기법을 소개하고, 제안하고자 하는 기법을 설명한다.

Keywords

References

  1. Dmitry Tsarkov and Ian Horrocks, FaCT++ description logic reasoner: System description, In Proc. of the Int. Joint Conf. on Automated Reasoning, IJCAR, 2006
  2. Evren Sirin, Bijan Parsia, Bernardo Cuenca Grau, Aditya Kalyanpur and Yarden Katz, Pellet: A practical OWL-DL reasoner, Journal of Web Semantics, 2007 https://doi.org/10.1016/j.websem.2007.03.004
  3. U. Hustadt, B. Motik U. Sattler, Reasoning in Description Logics with a Concrete Domain in the Framework of Resolution, Proc. of the 16th European Conference on Artificial Intelligence (ECAI 2004), Valencia, Spain, pp. 353-357, August, 2004
  4. F. Baader and W. Nutt, The Description Logic Handbook: Theory, Implementation, and Applications, pp. 43-95. Cambridge University Press, 2003
  5. Aditya Kalyanpur, Bijan Parsia, Bernardo Cuenca Grau and Evren Sirin, Justifications for Entailments in Expressive Description Logics, Technical report, 2006
  6. McGuinness, D. and Borgida, A., Explaining Subsumption in Description Logics, Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, pp. 816-821, 1995
  7. Schlobach, S. and Cornet, R., Non-Standard Reasoning Services for the Debugging of Description Logic Terminologies, Proceedings of IJCAI, 2003
  8. M. Dean and G. Schreiber, OWL Web Ontology Language Reference W3C Recommendation, http://www.w3.org/tr/owl-ref/. February 2004
  9. Johan de Kleer, Problem solving with the ATMS, Artificial Intelligence 28, pp. 163-196, 1986 https://doi.org/10.1016/0004-3702(86)90081-0
  10. Kenneth D. Forbus, Johan de Kleer, Building Problem Solvers, The MIT Press, 1993
  11. Johan de Kleer, A General Labeling Algorithm for Assumption based Truth Maintenance, Proceedings of the AAAI-88, 1988
  12. Debugging OWL Ontologies using Swoop, http://www. mindswap.org/2005/debugging/, 2005