SATPin: Axiom Pinpointing for Lightweight Description Logics Through Incremental SAT

Manthey, Norbert; Peñaloza, Rafael; Rudolph, Sebastian

doi:10.1007/s13218-020-00669-4

Cited by 3 publications

(1 citation statement)

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“…In this work, we propose a new method for computing deductive modules for EL ontologies to balance the computation cost and the result quality. Our method is inspired by the SAT-based approach (Arif, Mencía, and Marques-Silva 2015;Manthey, Peñaloza, and Rudolph 2016) developed to compute justifications, which are minimal sub-ontologies that derive a given entailment. The main idea of these SATbased methods is to encode the derivations of a given entailment as a set of Horn-clauses, then it enumerates all the justifications of this entailment by SAT tools or resolution (Kazakov and Skočovskỳ 2018).…”

Section: Introductionmentioning

confidence: 99%

Efficient Extraction of EL-Ontology Deductive Modules

Yang

Bidoit

2023

AAAI

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Because widely used real-world ontologies are often complex and large, one important challenge has emerged: designing tools for users to focus on sub-ontologies corresponding to their specific interests. To this end, various modules have been introduced to provide concise ontology views. This work concentrates on extracting deductive modules that preserve logical entailment over a given vocabulary. Existing deductive module proposals are either inefficient from a computing point of view or unsatisfactory from a quality point of view because the modules extracted are not concise enough. For example, minimal modules guarantee the most concise results, but their computation is highly time-consuming, while ⊥⊤∗-modules are easy to compute but usually contain many redundant items. To overcome computation cost and lack of quality, we propose to compute two kinds of deductive modules called pseudo-minimal modules and complete modules for EL-ontology. Our deductive module definitions rely on associating a tree representation with an ontology, and their computation is based on SAT encoding. Our experiments on real-world ontologies show that our pseudo-minimal modules are indeed minimal modules in almost all cases (98.9%), and computing pseudo-minimal modules is more efficient (99.79 times faster on average) than the state-of-the-art method Zoom for computing minimal modules. Also, our complete modules are more compact than ⊥⊤∗-modules, but their computation time remains comparable. Finally, note that our proposal applies to EL-ontologies while Zoom only works for EL-terminologies.

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Section: Introductionmentioning

confidence: 99%