Complexity of Inconsistency-Tolerant Query Answering in Datalog+/– under Cardinality-Based Repairs

Lukasiewicz, Thomas; Malizia, Enrico; Vaicenavičius, Andrius

doi:10.1609/aaai.v33i01.33012962

Cited by 12 publications

(13 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recently, other parameterized strategies have been proposed for the management of inconsistencies in knowledge bases. These strategies have been defined within frameworks that encompass DL-Lite logics, namely Datalog ± [30,38,55] (see also [56] for computational complexity analysis) and existential rules [8,9,54,59,60]. Parameterized inference defined in Datalog ±, called k-lazy semantics, is in the spirit of the k-suppoter semantics.…”

Section: Related Workmentioning

confidence: 99%

Handling inconsistency in partially preordered ontologies: the Elect method

Belabbès

Benferhat

Chomicki

2021

Journal of Logic and Computation

View full text Add to dashboard Cite

We focus on the problem of handling inconsistency in lightweight ontologies. We assume that the terminological knowledge base (TBox) is specified in DL-Lite and that the set of assertional facts (ABox) is partially preordered and may be inconsistent with respect to the TBox. One of the main contributions of this paper is the provision of an efficient and safe method, called Elect, to restore the consistency of the ABox with respect to the TBox. In the case where the assertional base is flat (i.e. no priorities are associated with the ABox) or totally preordered, we show that our method collapses with the well-known intersection ABox repair semantics and the non-defeated semantics, respectively. The semantic justification of the Elect method is obtained by first viewing a partially preordered ABox as a family of totally preordered ABoxes and then applying non-defeated inference to each of the totally preordered ABoxes. We introduce the notion of elected assertions which allows us to provide an equivalent characterization of the Elect method without explicitly generating all the totally preordered ABoxes. We show that computing the set of elected assertions is done in polynomial time with respect to the size of the ABox. The second part of the paper discusses how to go beyond the Elect method. In particular, we discuss to what extent the Elect method can be generalized to description logics that are more expressive than DL-Lite.

show abstract

Section: Related Workmentioning

confidence: 99%

Handling inconsistency in partially preordered ontologies: the Elect method

Belabbès

Benferhat

Chomicki

2021

Journal of Logic and Computation

View full text Add to dashboard Cite

show abstract

“…However, in some cases, it can be more appropriate to select only the most preferred repairs according to some criteria. Several different notions of preferred repair, based upon cardinality, priority levels, partial preorders, or weighted assertions, have been explored [49,14,28,5,39,6,39] and used as the basis for inconsistency-tolerant semantics.…”

Section: Examplementioning

confidence: 99%

“…In particular, there have been several works (see e.g. [41,40,5,39]) which have explored such semantics for existential rules (aka Datalog +/-) [20,42], which constitute another prominent class of ontology languages. Our treatment is based upon (and complementary to) a much more detailed tutorial chapter [12] and incorporates some more recent literature and perspectives for future work.…”

Section: Introductionmentioning

confidence: 99%

A Short Survey on Inconsistency Handling in Ontology-Mediated Query Answering

Bienvenu

2020

Künstl Intell

View full text Add to dashboard Cite

This paper provides a concise overview of the literature on inconsistency handling for ontologymediated query answering, a topic which has grown into an active area of research over the last decade. The focus of this survey is on the case where errors are localized in the data (i.e., the ontology is deemed reliable) and where inconsistency-tolerant semantics are employed with the aim of obtaining meaningful information from inconsistent knowledge bases.

show abstract

“…Inconsistency-tolerant semantics based on other kinds of preferred repairs have been investigated both in the database and DL or Datalog ± contexts, often with a focus on repairs that have maximal cardinality or weight (Lopatenko and Bertossi 2007;Du, Qi, and Shen 2013;Baget et al 2016;Lukasiewicz, Malizia, and Vaicenavicius 2019). However, such global optimality criteria lead to a higher computational complexity (typically ∆ P 2 [O(log n)]-hard).…”

Section: Related Workmentioning

confidence: 99%

Querying and Repairing Inconsistent Prioritized Knowledge Bases: Complexity Analysis and Links with Abstract Argumentation

Bourgaux¹

2020

Proceedings of the Seventeenth International Conference on Principles of Knowledge Representation and Reasoning

View full text Add to dashboard Cite

In this paper, we explore the issue of inconsistency handling over prioritized knowledge bases (KBs), which consist of an ontology, a set of facts, and a priority relation between conflicting facts. In the database setting, a closely related scenario has been studied and led to the definition of three different notions of optimal repairs (global, Pareto, and completion) of a prioritized inconsistent database. After transferring the notions of globally-, Pareto- and completion-optimal repairs to our setting, we study the data complexity of the core reasoning tasks: query entailment under inconsistency-tolerant semantics based upon optimal repairs, existence of a unique optimal repair, and enumeration of all optimal repairs. Our results provide a nearly complete picture of the data complexity of these tasks for ontologies formulated in common DL-Lite dialects. The second contribution of our work is to clarify the relationship between optimal repairs and different notions of extensions for (set-based) argumentation frameworks. Among our results, we show that Pareto-optimal repairs correspond precisely to stable extensions (and often also to preferred extensions), and we propose a novel semantics for prioritized KBs which is inspired by grounded extensions and enjoys favourable computational properties. Our study also yields some results of independent interest concerning preference-based argumentation frameworks.

show abstract

Complexity of Inconsistency-Tolerant Query Answering in Datalog+/– under Cardinality-Based Repairs

Cited by 12 publications

References 12 publications

Handling inconsistency in partially preordered ontologies: the Elect method

Handling inconsistency in partially preordered ontologies: the Elect method

A Short Survey on Inconsistency Handling in Ontology-Mediated Query Answering

Querying and Repairing Inconsistent Prioritized Knowledge Bases: Complexity Analysis and Links with Abstract Argumentation

Contact Info

Product

Resources

About