LAMAS&SR Workshop 2021 Workshop Paper
Knowledge Extraction for Multi-Agent System Communication
- David Toluhi
- Renate Schmidt
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LAMAS&SR Workshop 2021 Workshop Paper
AAAI Conference 2020 Conference Paper
This paper investigates the problem of forgetting in description logics with nominals. In particular, we develop a practical method for forgetting concept and role names from ontologies specified in the description logic ALCO, extending the basic ALC with nominals. The method always terminates, and is sound in the sense that the forgetting solution computed by the method has the same logical consequences with the original ontology. The method is so far the only approach to deductive forgetting in description logics with nominals. An evaluation of a prototype implementation shows that the method achieves a significant speed-up and notably better success rates than the LETHE tool which performs deductive forgetting for ALC-ontologies. Compared to FAME, a semantic forgetting tool for ALCOIH-ontologies, better success rates are attained. From the perspective of ontology engineering this is very useful, as it provides ontology curators with a powerful tool to produce views of ontologies.
AAAI Conference 2020 Conference Paper
We consider the following query answering problem: Given a Boolean conjunctive query and a theory in the Horn loosely guarded fragment, the aim is to determine whether the query is entailed by the theory. In this paper, we present a resolution decision procedure for the loosely guarded fragment, and use such a procedure to answer Boolean conjunctive queries against the Horn loosely guarded fragment. The Horn loosely guarded fragment subsumes classes of rules that are prevalent in ontology-based query answering, such as Horn ALCHOI and guarded existential rules. Additionally, we identify star queries and cloud queries, which using our procedure, can be answered against the loosely guarded fragment.
IJCAI Conference 2018 Conference Paper
This paper presents a practical method for computing solutions of concept forgetting in the description logic ALCOQ(neg, and, or), basic ALC extended with nominals, qualified number restrictions, role negation, role conjunction and role disjunction. The method is based on a non-trivial generalisation of Ackermann's Lemma, and attempts to compute either semantic solutions of concept forgetting or uniform interpolants in ALCOQ(neg, and, or). It is so far the only approach to concept forgetting in description logics with number restrictions plus nominals, as well as in description logics with ABoxes. Results of an evaluation with a prototypical implementation have shown that the method was successful in more than 90% of the test cases from a large corpus of biomedical ontologies. In only 13. 2% of these cases the solutions were semantic solutions.
AAAI Conference 2015 Conference Paper
Uniform interpolation and the dual task of forgetting restrict the ontology to a specified subset of concept and role names. This makes them useful tools for ontology analysis, ontology evolution and information hiding. Most previous research focused on uniform interpolation of TBoxes. However, especially for applications in privacy and information hiding, it is essential that uniform interpolation methods can deal with ABoxes as well. We present the first method that can compute uniform interpolants of any ALC ontology with ABoxes. ABoxes bring their own challenges when computing uniform interpolants, possibly requiring disjunctive statements or nominals in the resulting ABox. Our method can compute representations of uniform interpolants in ALCO. An evaluation on realistic ontologies shows that these uniform interpolants can be practically computed, and can often even be presented in pure ALC.