POAM: PARTIAL ALIGNMENT OF ONTOLOGIES IN DIALOG OF AGENTS BASED ON CONCEPT SIMILARITY

This paper describes a method to partially align ontologies in dialogs of agents which use different ontologies. The method aims at aligning in execution time only the concepts necessary to the agents fulfill the current dialog. Thus, reducing the number of concepts to be searched in the target ontology is a very important requirement for agents' mutual understanding. The proposed method (named POAM, acronym for Partial Ontology Alignment Method) uses syntactical and linguistic techniques to group concepts together. The underlying rationale of POAM is that a person perceives an object and immediately identifies some properties. Even never before seen objects can be interpreted independently of any class, because properties in the real world exist independently of any class. Hence, similarity between a pair of concepts is calculated based on the similarity of their properties. A set of measures including syntactical, structural and semantic ones are used to calculate similarity between the properties associated to the concepts. A property signature vector is created for each concept and the similarity between two concepts is given by the distance between the corresponding vectors in a high dimensional space. We demonstrate that POAM reduces the number of candidate mappings when aligning concepts in a dialog of agents by means of an evaluation using ontologies from the bibliographic domain of the Ontology Alignment Evaluation Initiative (OAEI). We also show that POAM performs satisfactorily well considering the quality of results measured with the precision and recall metrics.