Efficient Extraction of EL-Ontology Deductive Modules

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