Get my pizza right: Repairing missing is-a relations in ALC ontologies (extended version)

With the increased use of ontologies in semantically-enabled applications, the issue of debugging defects in ontologies has become increasingly important. These defects can lead to wrong or incomplete results for the applications. Debugging consists of the phases of detection and repairing. In this paper we focus on the repairing phase of a particular kind of defects, i.e. the missing relations in the is-a hierarchy. Previous work has dealt with the case of taxonomies. In this work we extend the scope to deal with ALC ontologies that can be represented using acyclic terminologies. We present algorithms and discuss a system

Abduction in {EL} via Translation to {FOL}

International audienceWe present a technique for performing TBox abduction in the description logic EL. The input problem is converted into first-order formulas on which a prime implicate generation technique is applied, then EL hypotheses are reconstructed by combining the generated positive and negative implicates

Completing and Debugging Ontologies: state of the art and challenges

As semantically-enabled applications require high-quality ontologies, developing and maintaining ontologies that are as correct and complete as possible is an important although difficult task in ontology engineering. A key step is ontology debugging and completion. In general, there are two steps: detecting defects and repairing defects. In this paper we discuss the state of the art regarding the repairing step. We do this by formalizing the repairing step as an abduction problem and situating the state of the art with respect to this framework. We show that there are still many open research problems and show opportunities for further work and advancing the field.Comment: 56 page

Why Not? Explaining Missing Entailments with Evee (Technical Report)

Understanding logical entailments derived by a description logic reasoner is not always straight-forward for ontology users. For this reason, various methods for explaining entailments using justifications and proofs have been developed and implemented as plug-ins for the ontology editor Prot\'eg\'e. However, when the user expects a missing consequence to hold, it is equally important to explain why it does not follow from the ontology. In this paper, we describe a new version of $\rm E{\scriptsize VEE}$, a Prot\'eg\'e plugin that now also provides explanations for missing consequences, via existing and new techniques based on abduction and counterexamples

Semantic Matchmaking as Non-Monotonic Reasoning: A Description Logic Approach

Matchmaking arises when supply and demand meet in an electronic marketplace, or when agents search for a web service to perform some task, or even when recruiting agencies match curricula and job profiles. In such open environments, the objective of a matchmaking process is to discover best available offers to a given request. We address the problem of matchmaking from a knowledge representation perspective, with a formalization based on Description Logics. We devise Concept Abduction and Concept Contraction as non-monotonic inferences in Description Logics suitable for modeling matchmaking in a logical framework, and prove some related complexity results. We also present reasonable algorithms for semantic matchmaking based on the devised inferences, and prove that they obey to some commonsense properties. Finally, we report on the implementation of the proposed matchmaking framework, which has been used both as a mediator in e-marketplaces and for semantic web services discovery

Connection-Minimal Abduction in EL\mathcal{EL} via Translation to {FOL}

International audienceAbduction in description logics finds extensions of a knowledge base to make it entail an observation. As such, it can be used to explain why the observation does not follow, to repair incomplete knowledge bases, and to provide possible explanations for unexpected observations. We consider TBox abduction in the lightweight description logic EL , where the observation is a concept inclusion and the background knowledge is a TBox, i.e., a set of concept inclusions. To avoid useless answers, such problems usually come with further restrictions on the solution space and/or minimality criteria that help sort the chaff from the grain. We argue that existing minimality notions are insufficient, and introduce connection minimality. This criterion follows Occam’s razor by rejecting hypotheses that use concept inclusions unrelated to the problem at hand. We show how to compute a special class of connection-minimal hypotheses in a sound and complete way. Our technique is based on a translation to first-order logic, and constructs hypotheses based on prime implicates. We evaluate a prototype implementation of our approach on ontologies from the medical domain

On a notion of abduction and relevance for first-order logic clause sets

I propose techniques to help with explaining entailment and non-entailment in first-order logic respectively relying on deductive and abductive reasoning. First, given an unsatisfiable clause set, one could ask which clauses are necessary for any possible deduction (\emph{syntactically relevant}), usable for some deduction (\emph{syntactically semi-relevant}), or unusable (\emph{syntactically irrelevant}). I propose a first-order formalization of this notion and demonstrate a lifting of this notion to the explanation of an entailment w.r.t some axiom set defined in some description logic fragments. Moreover, it is accompanied by a semantic characterization via \emph{conflict literals} (contradictory simple facts). From an unsatisfiable clause set, a pair of conflict literals are always deducible. A \emph{relevant} clause is necessary to derive any conflict literal, a \emph{semi-relevant} clause is necessary to derive some conflict literal, and an \emph{irrelevant} clause is not useful in deriving any conflict literals. It helps provide a picture of why an explanation holds beyond what one can get from the predominant notion of a minimal unsatisfiable set. The need to test if a clause is (syntactically) semi-relevant leads to a generalization of a well-known resolution strategy: resolution equipped with the set-of-support strategy is refutationally complete on a clause set $N$ and SOS $M$ if and only if there is a resolution refutation from $N\cup M$ using a clause in $M$. This result non-trivially improves the original formulation. Second, abductive reasoning helps find extensions of a knowledge base to obtain an entailment of some missing consequence (called observation). Not only that it is useful to repair incomplete knowledge bases but also to explain a possibly unexpected observation. I particularly focus on TBox abduction in \EL description logic (still first-order logic fragment via some model-preserving translation scheme) which is rather lightweight but prevalent in practice. The solution space can be huge or even infinite. So, different kinds of minimality notions can help sort the chaff from the grain. I argue that existing ones are insufficient, and introduce \emph{connection minimality}. This criterion offers an interpretation of Occam's razor in which hypotheses are accepted only when they help acquire the entailment without arbitrarily using axioms unrelated to the problem at hand. In addition, I provide a first-order technique to compute the connection-minimal hypotheses in a sound and complete way. The key technique relies on prime implicates. While the negation of a single prime implicate can already serve as a first-order hypothesis, a connection-minimal hypothesis which follows \EL syntactic restrictions (a set of simple concept inclusions) would require a combination of them. Termination by bounding the term depth in the prime implicates is provable by only looking into the ones that are also subset-minimal. I also present an evaluation on ontologies from the medical domain by implementing a prototype with SPASS as a prime implicate generation engine.Ich schlage Techniken vor, die bei der Erklärung von Folgerung und Nichtfolgerung in der Logik erster Ordnung helfen, die sich jeweils auf deduktives und abduktives Denken stützen. Erstens könnte man bei einer gegebenen unerfüllbaren Klauselmenge fragen, welche Klauseln für eine mögliche Deduktion notwendig (\emph{syntaktisch relevant}), für eine Deduktion verwendbar (\emph{syntaktisch semi-relevant}) oder unbrauchbar (\emph{syntaktisch irrelevant}). Ich schlage eine Formalisierung erster Ordnung dieses Begriffs vor und demonstriere eine Anhebung dieses Begriffs auf die Erklärung einer Folgerung bezüglich einer Reihe von Axiomen, die in einigen Beschreibungslogikfragmenten definiert sind. Außerdem wird sie von einer semantischen Charakterisierung durch \emph{Konfliktliteral} (widersprüchliche einfache Fakten) begleitet. Aus einer unerfüllbaren Klauselmenge ist immer ein Konfliktliteralpaar ableitbar. Eine \emph{relevant}-Klausel ist notwendig, um ein Konfliktliteral abzuleiten, eine \emph{semi-relevant}-Klausel ist notwendig, um ein Konfliktliteral zu generieren, und eine \emph{irrelevant}-Klausel ist nicht nützlich, um Konfliktliterale zu generieren. Es hilft, ein Bild davon zu vermitteln, warum eine Erklärung über das hinausgeht, was man aus der vorherrschenden Vorstellung einer minimalen unerfüllbaren Menge erhalten kann. Die Notwendigkeit zu testen, ob eine Klausel (syntaktisch) semi-relevant ist, führt zu einer Verallgemeinerung einer bekannten Resolutionsstrategie: Die mit der Set-of-Support-Strategie ausgestattete Resolution ist auf einer Klauselmenge $N$ und SOS $M$ widerlegungsvollständig, genau dann wenn es eine Auflösungswiderlegung von $N\cup M$ unter Verwendung einer Klausel in $M$ gibt. Dieses Ergebnis verbessert die ursprüngliche Formulierung nicht trivial. Zweitens hilft abduktives Denken dabei, Erweiterungen einer Wissensbasis zu finden, um eine implikantion einer fehlenden Konsequenz (Beobachtung genannt) zu erhalten. Es ist nicht nur nützlich, unvollständige Wissensbasen zu reparieren, sondern auch, um eine möglicherweise unerwartete Beobachtung zu erklären. Ich konzentriere mich besonders auf die TBox-Abduktion in dem leichten, aber praktisch vorherrschenden Fragment der Beschreibungslogik \EL, das tatsächlich ein Logikfragment erster Ordnung ist (mittels eines modellerhaltenden Übersetzungsschemas). Der Lösungsraum kann riesig oder sogar unendlich sein. So können verschiedene Arten von Minimalitätsvorstellungen helfen, die Spreu vom Weizen zu trennen. Ich behaupte, dass die bestehenden unzureichend sind, und führe \emph{Verbindungsminimalität} ein. Dieses Kriterium bietet eine Interpretation von Ockhams Rasiermesser, bei der Hypothesen nur dann akzeptiert werden, wenn sie helfen, die Konsequenz zu erlangen, ohne willkürliche Axiome zu verwenden, die nichts mit dem vorliegenden Problem zu tun haben. Außerdem stelle ich eine Technik in Logik erster Ordnung zur Berechnung der verbindungsminimalen Hypothesen in zur Verfügung korrekte und vollständige Weise. Die Schlüsseltechnik beruht auf Primimplikanten. Während die Negation eines einzelnen Primimplikant bereits als Hypothese in Logik erster Ordnung dienen kann, würde eine Hypothese des Verbindungsminimums, die den syntaktischen Einschränkungen von \EL folgt (einer Menge einfacher Konzeptinklusionen), eine Kombination dieser beiden erfordern. Die Terminierung durch Begrenzung der Termtiefe in den Primimplikanten ist beweisbar, indem nur diejenigen betrachtet werden, die auch teilmengenminimal sind. Außerdem stelle ich eine Auswertung zu Ontologien aus der Medizin vor, Domäne durch die Implementierung eines Prototyps mit SPASS als Primimplikant-Generierungs-Engine