On the Merging of Domain-Specific Heterogeneous Ontologies using Wordnet and Web Pattern-based Queries
This addresses interoperability issues in semantic web and related fields, but it appears incremental as it builds on existing methods like WordNet and web queries.
The paper tackles the problem of semantic heterogeneity in domain-specific ontologies by presenting a multi-purpose framework that uses WordNet and web pattern-based queries to discover and correct semantic relations, merge ontologies, and enrich WordNet with missing concepts, with experimental validation showing comparisons to state-of-the-art systems.
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.