Abstract
Repair techniques are used for reasoning in presence of inconsistencies. Such techniques rely on optimisations to avoid the computation of all repairs while certain applications need the generation of all repairs. In this paper, we show that the problem of all repair computation is not trivial in practice. To account for a scalable solution, we provide an incremental approach for the computation of all repairs when the conflicts have a cardinality of at most three. We empirically study its performance on generated knowledge bases (where the knowledge base generator could be seen as a secondary contribution in itself).
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Notes
- 1.
The algorithms avoid the problem of derivation loss [19] which is important for the completeness of our approach. Note that in Hecham et al. [19] the authors discuss how finding all derivations for an atom is practically feasible despite the problem being exponential for combined complexity but polynomial for data complexity.
- 2.
The set of restricted conflicts by a set U is the set containing each intersection of a conflict with U. Namely, it is equal to \(\{ X \cap U \mid X \in Conflict(\mathcal {K})\}.\)
- 3.
- 4.
A subrepair of U w.r.t. \(\mathcal {A}\) is a subset of a repair of U w.r.t. \(\mathcal {A}\).
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The second author acknowledges the support of the Docamex project, funded by the French Ministry of Agriculture.
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Yun, B., Croitoru, M. (2020). An Incremental Algorithm for Computing All Repairs in Inconsistent Knowledge Bases. In: Alam, M., Braun, T., Yun, B. (eds) Ontologies and Concepts in Mind and Machine. ICCS 2020. Lecture Notes in Computer Science(), vol 12277. Springer, Cham. https://doi.org/10.1007/978-3-030-57855-8_3
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