Approach of Ontology Learning from Relational Database Based on FCA
一种基于FCA的面向关系数据库的本体学习方法

Ontology learning is a process,which extracts semantic information from the existing data model and generates ontology using a set of predefined mapping rules. Relational database is the main model of data access and management,and extracting ontology from relational database is one of the research hotspots in ontology engineering field. A common method adopted by the domestic and foreign scholars is that ontology is constructed by using mapping rules between E-R model and ontology elements. But this method is subjective and it goes against the application of ontology. To address this issue, an approach of ontology learning from relational database based on formal concept analysis was proposed,which could obtain the hierarchical relation of concept and semantic relation of data objectively. The proposed method not only keeps the semantic information of relational data tables, but also shows the advantage of FCA in automatic extraction of semantic information. Thus the quality of final ontology is improved and the application field of ontology is extended. A case study of the proposed method combined with materials service safety database was also presented.