Abstract
Ontology matching is the process of finding correspondences between semantically related entities of different ontologies. We need to apply this process to solve the heterogeneity problems between different ontologies. Some ontologies may contain thousands of entities which make the ontology matching process very complex in terms of space and time requirements. This paper presents a framework that reduces the search space by removing entities (classes, properties) that have less probability of being matched. In order to achieve this goal we have introduced a matching strategy that uses multi matching techniques specifically; string, structure, and linguistic matching techniques. The results obtained from this framework have indicated a good quality matching outcomes in a low time requirement and a low search space in comparisons with other matching frameworks. It saves from the search space from (43% - 53%), and saves on the time requirement from (38% - 45%).
Highlights
In the current World Wide Web (WWW) computers and machines have no idea about the semantic of the information that are transferred through the web; the transferred information are not machine understandable
To reduce the search space and time requirement of the ontology matching process, we present in this paper an ontology matching framework
For the purpose of evaluating our proposed matching system (PMS) we have developed a matching system called (Traditional Matching System) TMS that is based on the work of some existing ontology matching systems such as Naive Ontology Mapping (NOM) [7], PROMPT [15], Anchor-PROMPT [14] and GLUE [5]
Summary
In the current World Wide Web (WWW) computers and machines have no idea about the semantic of the information that are transferred through the web; the transferred information are not machine understandable. The generation of the WWW is called a Semantic Web. The role of the computers in the Semantic Web is to present the information, but for the computers to read and process the information in the WebPages, and extract knowledge from this information. The computer can understand the information in the Semantic Web by using a data structure called Ontology. Different people may develop different ontologies that describe a particular domain; this causes heterogeneity problems between ontologies that describe the same domain. In general different ontologies for a specific domain may use different data formats, modeling languages and structures to represent certain knowledge. Ontology matching is the process of finding correspondences between semantically related entities of different ontologies These correspondences stand for different relations such as equivalence, more general, or disjointness, between ontologies entities
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