Semantic adaptation of knowledge representation systems

Abstract

Due to the worldwide diversity of enterprises, a high number of ontologies representing the same segment of reality which are not semantically coincident have appeared. To solve this problem, a possible solution is to use a reference ontology to be the intermediary in the communications between the community enterprises and to outside. Since semantic mappings between enterprise’s ontologies are established, this solution allows each of the enterprises to keep internally its own ontology and semantics unchanged. However information systems are not static, thus established mappings become obsolete with time. This paper’s presents a PhD research with the objective to identify a suitable approach that combines semantic mappings with user’s feedback, providing an automatic learning to ontologies & enabling auto-adaptability and, consequently, dynamism to the information systems.