On the Merging of Domain-Specific Heterogeneous Ontologies using Wordnet and Web Pattern-based Queries

April 30, 2020 Β· Declared Dead Β· πŸ› Journal of Information & Knowledge Management

πŸ‘» CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

Authors M. Maree, M. Belkhatir arXiv ID 2005.00158 Category cs.IR: Information Retrieval Cross-listed cs.AI, cs.CL Citations 3 Venue Journal of Information & Knowledge Management Last Checked 4 months ago
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.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

πŸ“œ Similar Papers

In the same crypt β€” Information Retrieval

Died the same way β€” πŸ‘» Ghosted