语义网中基于机器学习的本体映射研究

Research on Ontology Mapping based on Machine Learning for Semantic Web

本体映射是解决语义网中不同本体间的知识共享和重用问题的有效方法。本论文从解决语义网中本体的各种异构问题出发,同时考虑到目前的本体大多映射效率不高、映射结果不够准确的问题,在对比分析了本体映射各种方法的基础上,重点研究了基于机器学习技术的本体映射机制,提出了一种高效地建立本体映射的方法及系统框架,该方法利用机器学习技术来提高本体映射的自动化程度,利用综合评判技术来修正映射结果,以提高本体映射的准确率。

Ontology mapping is an effective method of solving the problem of knowledge sharing and knowledge reuse among different ontology on semantic web. This paper based on solving the various problems of heterogeneous among ontology, taking into account the most current ontology mapping efficiency is not high, the results of ontology mapping is not accurate enough, either. To address the above issues, this paper compared and analyzed various methods of ontology mapping, studied ontology mapping mechanism based on machine learning technology, proposed efficient ontology mapping method and system framework. The method adopts machine learning techniques to enhance the degree of automation ontology mapping, uses comprehensive evaluation technology to amend the results of ontology mapping, with the result of improving the accuracy of ontology mapping.