User-guided Repairing of Inconsistent Knowledge Bases

International audienceRepairing techniques for relational databases have leveraged in- tegrity constraints to detect and then resolve errors in the data. User guidance has started to be employed in this setting to avoid a prohibitory exploration of the search space of solutions. In this pa- per, we present a user-guided repairing technique for Knowledge Bases (KBs) enabling updates suggested by the users to resolve errors. KBs exhibit more expressive constraints with respect to relational tables, such as tuple-generating dependencies (TGDs) and negative rules (a form of denial constraints). We consider TGDs and a notable subset of denial constraints, named contra- diction detecting dependencies (CDDs). We propose user-guided polynomial-delay algorithms that ensure the repairing of the KB in the extreme cases of interaction among these two classes of constraints. To the best of our knowledge, such interaction is so far unexplored even in repairing methods for relational data. We prove the correctness of our algorithms and study their feasibility in practical settings. We conduct an extensive experimental study on synthetically generated KBs and a real-world inconsistent KB equipped with TGDs and CDDs. We show the practicality of our proposed interactive strategies by measuring the actual delay time and the number of questions required in our interactive framework

Computational Complexity of Strong Admissibility for Abstract Dialectical Frameworks

Abstract dialectical frameworks (ADFs) have been introduced as a formalism for modeling and evaluating argumentation allowing general logical satisfaction conditions. Different criteria used to settle the acceptance of arguments arecalled semantics. Semantics of ADFs have so far mainly been defined based on the concept of admissibility. Recently, the notion of strong admissibility has been introduced for ADFs. In the current work we study the computational complexityof the following reasoning tasks under strong admissibility semantics. We address 1. the credulous/skeptical decision problem; 2. the verification problem; 3. the strong justification problem; and 4. the problem of finding a smallest witness of strong justification of a queried argument

A Datalog+/-Domain-Specific Durum Wheat Knowledge Base

International audienceWe consider the application setting where a domain-specific knowledge base about Durum Wheat has been constructed by knowledge engineers who are not experts in the domain. This knowledge base is prone to inconsistencies and incompleteness. The goal of this work is to show how the state of the art knowledge representation formalism called Datalog± can be used to cope with such problems by (1) providing inconsistency-tolerant techniques to cope with inconsistency, and (2) providing an expressive logical language that allows representing incomplete knowledge