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Ontology Mapping and Research of Data Integration Based on the Ontoly

Author: ZhouJian
Tutor: JiangBo
School: Zhejiang Technology and Business University
Course: Computer Software and Theory
Keywords: Ontology mapping Data Integration Machine Learning Naive Bayes
CLC: TP391.1
Type: Master's thesis
Year: 2010
Downloads: 119
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Abstract


With the rapid development of science and technology, more and more areas of information technology for data management, compared with the previous data processing, streamline operations, improve work efficiency. However, with the continuous progress of the information technology, data storage is increasingly fragmented and diverse forms, leading to \Different ontology-based information system in the exchange of information must be able to understand each other, ontology mapping technology demand. Ontology mapping technology from heterogeneous database schema mapping technology, after years of research has made great progress, but there are still mapping heuristic information accuracy and low degree of automation. The basis of the analysis of heterogeneous data integration and ontology background data integration method based on ontology mapping, to better address the heterogeneous and semantic conflicts in heterogeneous data integration. In this method, the use of a hybrid body construction model by mapping to establish the corresponding relationship between the heterogeneous data sharing. Of this study include: (1) integration technology based on ontology mapping attribute mapping method and its concept mapping. Current ontology mapping research is mainly focused on the concept map, found by mapping the corresponding relationship between the two body concept, cause results not comprehensive, property mapping method based on ontology mapping, and concept mapping methods with attributes integration technology mapping method. The method uses the concept of similarity and the concept of attribute similarity calculation method, the formation of semantic similarity calculation method by the A * algorithm to select the appropriate component weights, Finally, according to this method to find the mapping relationship between the body. More comprehensive than the previous method of semantic similarity method screenings semantic relationships between the body, in order to better service for ontology mapping. (2) a semi-automated global ontology construction method. Can not achieve complete intelligent mapping between body Therefore, this article introduces a similarity calculation between local ontologies, ontology similarity calculation method proposed by the front, provide a possible match candidate for the extraction of the global vocabulary the list of results, improve the success rate and efficiency of the global body build. (3) the heterogeneous data integration framework based on ontology mapping successfully applied to the integration of modern digital community information. Analysis of existing heterogeneous data integration architecture, choose the mode of middleware integration, ontology-based heterogeneous data integration, system architecture design, JAVA and protege ontology development tools for critical basis The modules for the realization. This study show that, through the use of a variety of mapping methods, the concept attributes available information integrated treatment methods such as the use of machine learning in the mapping, can effectively improve the automatic mapping effect in the body, reduce manual workload mapping.

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