Discovering semantic relations from unstructured data for ontology enrichment: Asssociation rules based approach

Ontologies have been used in information system development as one of the main knowledge representation tool. Ontologies are composed by concepts, a hierarchy, arbitrary relations between concepts, and possibly other axioms. However, ontology building is a time-consuming process, and it should be supported by automatic finding of interesting, possible relationships among concepts. This paper describes how an analysis of co-occurrences of concepts in unstructured sources of information can be used to provide interesting relationships for enriching ontological structures. We apply association rule theory to construct ontological concept relations and evaluate the importance of such relations for supporting the building process of a domain ontology. Preliminary results were collected using scientific published papers from the building and construction sector, which were used as an input for applying our method. A knowledge browsing environment was developed in order to support the analysis process.

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