چكيده به لاتين
Ontology is a common vocabulary for modeling a domain of interest that describes the type of objects / concepts, their properties, and their relationships. It is also a structure for storing, retrieving and sharing knowledge, and is used in various branches of computer science such as: semantic web, artificial intelligence, software engineering, databases and natural language processing. Since there is no relational algebra in database designs, we are therefore interested in ontology because of its high expressiveness and semantic theoretical model. Ontological matching is an important practice in modern ontology engineering because it supports heterogeneous environments in which ontologies are designed, developed, and are to be implemented. Ontology engineering requires ontology matching (OM) support because ontology engineering must deal with multiple, distributed and evolved ontologies. Different approaches require semantic interoperability, for example, agreement between the ontologies of the two agents, as well as adaptation of the ontology, for example, to the integration process and alignment of the ontologies for effective communication between the agents across a wide range of applications.In the ontology matching, the correspondences between the ontology entities(element level) are determined using distance/similarity measures. The concept of similarity measure is used in various scientific fields such as decision making , pattern recognition , machine learning and market forecasting. Also topological methods (geology) Applied to areas such as semantics. First, we explain some of the existing fuzzy string similarity measure, then selectively apply a voting strategy using these fuzzy string similarity measure to integrate them as an alternative solution in Consider improving the similarity methods available.Several samples have been tested to evaluate the above strategy.
