Research On Approaches Of FCA-based Ontology Building And Mapping

Ontology is the explicit and formal description of share conceptualization. It can provide semantic meaning through relations between concepts. As a fine model for presenting hierarchy and semantic meaning of concepts, ontology has been applied widely in the fields of computer science.With the abroad application of ontology,ontology development also face some problem of reality.Such as how to build ontology conveniently,the problem of ontology formal description ,the problem of ontology integration and the ontology application . On the basis of a brief analysis of ontology research status and hotspit,this thesis focus on two key problem of ontology research: ontology building and ontology mapping. We propose approaches of FCA-based ontology building and mapping through introduce the method of formal concept analysis.The primary work and contributions of this thesis are as follows:1. The research of ontology theories and formal concept analysis. Firstly,this thesis introduce the basic concepts of ontology,including the definitions of ontology,the description language of ontology and ontolgy classifications. Secondly the thesis introduce the theories of formal concept analysis and concept lattice.Lastly,analyze the differences and relations between ontology and formal concept analysis.2. Research on approaches of FCA-based ontology buildingAfter researching the basic criterion and methods of ontology building,a domain ontology building framework based on formal concept analysis is proposed. This method constructs concept lattice by adding objects (classes) and properties and to visualizes ontology by concept lattice,then builds original ontology. The aproach that visualizing concepts and relations between concepts is easily comprehend by people.3. Research on approaches of FCA-based ontology mappingThis thesis introduce the formal concept analysis into ontology mapping,and a FCA-based ontology mapping method is proposed.The attributes of classes in different ontologies is organized in a partial order set by means of a thesaurus, then the corresponding formal context and concept lattice is created. A similarity computational model based on concept lattice is introduced, which allow us to compute concept similarity according to the meet-irreducible elements. The result of analysis in theory and experiment proves the FCA-based method have higher precision than the method based on traditional feature model. To compute the similarity between rough concepts, this thesis introduce the rough set to formal concept analysis and defines the equivalence relationships in FCA, proposes a RFCA-based similarity computional model.