Redundancy-free Verbalization of Individuals for Ontology Validation
E. V. Vinu, P Sreenivasa Kumar

TL;DR
This paper introduces a semantic reduction method for OWL axioms that produces redundancy-free natural language descriptions of ontology individuals, enhancing human understanding and validation.
Contribution
It proposes a novel semantic reduction approach at the logical level to generate more concise, redundancy-free natural language descriptions of ontology entities, especially individuals.
Findings
Semantic reduction improves description clarity
Redundancy-free descriptions aid ontology validation
Case study confirms practical usefulness
Abstract
We investigate the problem of verbalizing Web Ontology Language (OWL) axioms of domain ontologies in this paper. The existing approaches address the problem of fidelity of verbalized OWL texts to OWL semantics by exploring different ways of expressing the same OWL axiom in various linguistic forms. They also perform grouping and aggregating of the natural language (NL) sentences that are generated corresponding to each OWL statement into a comprehensible structure. However, no efforts have been taken to try out a semantic reduction at logical level to remove redundancies and repetitions, so that the reduced set of axioms can be used for generating a more meaningful and human-understandable (what we call redundancy-free) text. Our experiments show that, formal semantic reduction at logical level is very helpful to generate redundancy-free descriptions of ontology entities. In this paper,…
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Taxonomy
TopicsSemantic Web and Ontologies · Biomedical Text Mining and Ontologies · Cognitive Computing and Networks
