[Submitted on 30 Apr 2020]

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Abstract: Ontologies form the basic interest in various computer science disciplines
such as semantic web, information retrieval, database design, etc. They aim at
providing a formal, explicit and shared conceptualization and understanding of
common domains between different communities. In addition, they allow for
concepts and their constraints of a specific domain to be explicitly defined.
However, the distributed nature of ontology development and the differences in
viewpoints of the ontology engineers have resulted in the so called “semantic
heterogeneity” between ontologies. Semantic heterogeneity constitutes the major
obstacle against achieving interoperability between ontologies. To overcome
this obstacle, we present a multi-purpose framework which exploits the WordNet
generic knowledge base for: i) Discovering and correcting the incorrect
semantic relations between the concepts of the ontology in a specific domain.
This step is a primary step of ontology merging. ii) Merging domain-specific
ontologies through computing semantic relations between their concepts. iii)
Handling the issue of missing concepts in WordNet through the acquisition of
statistical information on the Web. And iv) Enriching WordNet with these
missing concepts. An experimental instantiation of the framework and
comparisons with state-of-the-art syntactic and semantic-based systems validate
our proposal.