A New Algorithm for Fully Automated Ontology Merging Based on Semantics Using WordNet
Siham Amrouch, Sihem Mostefai
International Journal of Information Studies, Vol. 4, No. 1, 2012.
DOI: 
Link: https://www.dline.info/ijis/fulltext/v4n1/ijisv4n1_5.pdf
Abstract:
In the last decade, ontologies became very relevant tools for knowledge management and engineering because
of their potential power to embed semantic modelling. They explicitly specify the concepts of a domain and their semantic
relationships. However, ontologies are designed and developed by several designers and developers according to their
special needs and requirements. Hence, we may always find that the same domain or even related domains are modelled by
different ontologies. We may also find that some ontologies model overlapping domains, resulting sometimes in redundancies
and/or inconsistencies between them. So, to create a common knowledge base and to avoid overlapping between existing
ontologies, we have opted for ontology merging. The contribution presented in this paper provides a new algorithm for fully
automated ontology merging that provides complete, consistent and coherent global merged ontology. This automation is
handled by the semantic integration during the similarity identification stage. This characteristic features the main difference
of our contribution with regards to most of the existing algorithms for ontology merging, such as CHIMAERA, PROMPT,
ONION, FCA-Merge, GLUE, etc. Our algorithm combines lexical and semantic measures for identifying similar concepts that
have to be merged into a single one in the resulting ontology. In this stage, it combines two different sub-modules, the first one
analyses the conceptsâ€™ names, the second one their properties. If the first sub-module fails to find mappings the second one will
accomplish the task. Hence the performances of the algorithm will be better.