Design And Implementation Based On Relational Database Of Ontology Semiautomatic Construction System

In the semantic web, ontology(Ontology)has a very important position,it is the foundation to solve the semantic level knowledge sharing, reuse and exchange. However, most rely onexperts in the field of manual construction of ontology. The manual construction has low degree of automation, expert dependence, ontology construction defects such as slow body,restricted the development of semantic web and related applications. Therefore, how to construct a semi-automatic, automatic ontology is an important issue in related research in semantic web. This paper has done the following work:(1)Put forward a method of constructing OWL ontology based on relational database, the main idea is based on ontology and relational model on the formal definition, through a detailed analysis of the relationship between the mode of information, defining a series of mapping from relationship mode to ontology mapping rules, based on these rules, while buildingontology with the features of the OWL language grammar. To solve most of the currentontology relies on experts in the field of manual editing of the problem.(2)Research on ontology integration method based on concept similarity. Firstly, the similarity calculation between concepts in the ontology similarity calculation method, using the semantic similarity calculation based on WordNet formula, the edit distance based on the formula and the formula to calculate the similarity of ontology based context attributes, generatingsimilarity matrix. Then use hierarchical clustering algorithm to find similar concepts. Finally,using heuristic rule to merge similar concepts. To solve the ontology merging and concept hierarchy, distributed heterogeneous mining problems.(3)Based on Spring MVC framework, using B/S architecture, using the distributed map database of bigdata open source as a storage medium body, semi automatic construction system of developing an ontology. This system implements the relational data cleaning data duplicate removal, ontology semi-automatic construction of ontology, massive data storage, data query and browse the system function, posted on the Internet, has a friendly user interface, and for a variety of semantic related services(semantic search, QA etc.) to provide support, become the cornerstone of the semantic web the application layer.