A framework for ontology integration based on genetic algorithm
A framework for ontology integration based on genetic algorithm
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DOI：
10.3233/ifs-151872
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发表时间：
2016
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影响因子：
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通讯作者：
Lingyu Zhang;Bairui Tao
中科院分区：
文献类型：
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作者：
Lingyu Zhang;Bairui Tao
本体集成是将异构本体中的信息集成到一个本体中的一项重要工作。现有的本体集成方法不能有效地利用真实的世界中普遍存在的非1-1映射。而且，这些方法只提出了对具有映射的概念对进行集成，而没有给出具体的集成操作，因此，这些方法不能描述一个完整的本体集成框架。为此，本文提出了一种基于遗传算法的本体集成框架OI-GA。在本体集成过程中，OI-GA首先根据相似性度量建立本体之间的映射。其次，OI-GA从映射中找出所有的非1-1映射，并提供了一种进化的方法来提取1-1映射。最后，将属于不同本体的所有概念集成到一个新的知识库中，称为集成本体。实验结果表明，OI-GA在优化映射集和集成来自真实的世界的本体方面具有良好的性能。
Ontology integration is an important work when integrating information from heterogeneous ontologies into an ontology. The existing methods about ontology integration cannot effectively make full use of non-1-1 mappings, which are very common in the real world. Furthermore, these methods only stated that the concept-pairs with mappings should be integrated, but not gave the specific operations for it. Therefore, these methods cannot describe a complete framework for ontology integration. To this end, this paper proposes a framework for Ontology Integration based on Genetic Algorithm, called OI-GA. During the process of integrating ontologies, OI-GA firstly creates mappings between them based on similarity measures. Next, OI-GA finds out all the non-1-1 mappings from mappings, and provides an evolutionary method to extract 1-1 mappings from them. Finally, all the concepts belonging to different ontologies are integrated into a new knowledge base called integrated ontology. Experimental results indicate that OI-GA performs encouragingly well in the optimization of mapping set as well as in the integration of ontologies from the real world.