Non-Objection Inference for Inconsistency-Tolerant Query Answering

Repair based techniques are a standard way of dealing with inconsistency in the context of ontology based data access.We propose a novel nonobjection inference relation (along with its variants) where a query is considered as valid if it follows from at least one repair and it is consistent with all the repairs. These inferences are strictly more productive than universal inference while preserving the consistency of its set of conclusions. We study the productivity and properties of the new inferences. We also give experimental results of the proposed nonobjection inference.

[1]  Sarit Kraus,et al.  Nonmonotonic Reasoning, Preferential Models and Cumulative Logics , 1990, Artif. Intell..

[2]  Diego Calvanese,et al.  The DL-Lite Family and Relations , 2009, J. Artif. Intell. Res..

[3]  Didier Dubois,et al.  Inconsistency Management and Prioritized Syntax-Based Entailment , 1993, IJCAI.

[4]  Maurizio Lenzerini,et al.  Inconsistency-tolerant query answering in ontology-based data access , 2015, J. Web Semant..

[5]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[6]  Diego Calvanese,et al.  Evolution of DL-Lite Knowledge Bases , 2010, SEMWEB.

[7]  Didier Dubois,et al.  Some Syntactic Approaches to the Handling of Inconsistent Knowledge Bases: A Comparative Study Part 1: The Flat Case , 1997, Stud Logica.

[8]  Thomas Lukasiewicz,et al.  From Classical to Consistent Query Answering under Existential Rules , 2015, AMW.

[9]  Carsten Lutz,et al.  The Combined Approach to OBDA: Taming Role Hierarchies using Filters , 2012, SSWS+HPCSW@ISWC.

[10]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[11]  Salem Benferhat,et al.  How to Select One Preferred Assertional-Based Repair from Inconsistent and Prioritized DL-Lite Knowledge Bases? , 2015, IJCAI.

[12]  Diego Calvanese,et al.  Tractable Reasoning and Efficient Query Answering in Description Logics: The DL-Lite Family , 2007, Journal of Automated Reasoning.

[13]  Madalina Croitoru,et al.  A General Modifier-Based Framework for Inconsistency-Tolerant Query Answering , 2016, KR.

[14]  François Goasdoué,et al.  Querying Inconsistent Description Logic Knowledge Bases under Preferred Repair Semantics , 2014, Description Logics.

[15]  Maurizio Lenzerini,et al.  Inconsistency-Tolerant Semantics for Description Logics , 2010, RR.

[16]  Meghyn Bienvenu,et al.  On the Complexity of Consistent Query Answering in the Presence of Simple Ontologies , 2012, AAAI.

[17]  Thomas Lukasiewicz,et al.  Inconsistency Handling in Datalog+/- Ontologies , 2012, ECAI.

[18]  Bernhard Nebel,et al.  Base Revision Operations and Schemes: Semantics, Representation and Complexity , 1994, ECAI.

[19]  Joseph Y. Halpern,et al.  Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence , 2014, AAAI 2014.

[20]  Riccardo Rosati,et al.  Tractable Approximations of Consistent Query Answering for Robust Ontology-based Data Access , 2013, IJCAI.

[21]  M. Tamer Özsu.  Synthesis Lectures on Data Management , 2010 .

[22]  Jan Chomicki,et al.  Consistent Query Answering: Five Easy Pieces , 2007, ICDT.

[23]  Hai Wan,et al.  Query Answering with Inconsistent Existential Rules under Stable Model Semantics , 2016, AAAI.

[24]  Leopoldo E. Bertossi,et al.  Database Repairing and Consistent Query Answering , 2011, Database Repairing and Consistent Query Answering.

[25]  Riccardo Rosati,et al.  On the Complexity of Dealing with Inconsistency in Description Logic Ontologies , 2011, IJCAI.

[26]  Klaudia Frankfurter.  Computers And Intractability A Guide To The Theory Of Np Completeness , 2016 .