Schema Evolution publication categorizer

Latest research efforts on the semi-automatic coordination of ontologies “touch” on the mapping /merging of ontologies using the whole breadth of available knowledge. Addressing this issue, this paper presents the HCONE-merge approach, which is further extended towards automating the merging process. HCONE-merge makes use of the intended informal meaning of concepts by mapping them to WordNet senses using the Latent Semantic Indexing (LSI) method. Based on these mappings and using the reasoning services of Description Logics, HCONE-merge automatically aligns and then merges ontologies. Since the mapping of concepts to their intended meaning is an essential step of the HCONE-merge approach, this paper explores the level of human involvement required for mapping concepts of the source ontologies to their intended meanings. We propose a series of methods for ontology mapping (towards merging) with varying degrees of human involvement and evaluate them experimentally. We conclude that, although an effective fully automated process is not attainable, we can reach a point where ontology merging can be carried out efficiently with minimum human involvement.