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An Approach for the Emerging Ontology Alignment based on the Bees Colonies

机译：基于蜂群的新兴本体对齐方法

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This work is a research in the field of Ontologies Integration from the point of view of Ontology Mining based on Services. Specifically, the work focuses on an automatic suggestion of ontological alignments for users. The Ontology Mining area (OM) is very recent, due to the current trend of using ontologies as a mechanism for representing knowledge, which has created a wide field to explore and extract knowledge. The problem lies in the comparison of existing ontologies, in order to use them together, that is, finding their semantic equivalences. There are different techniques for ontologies alignment as a form of ontological comparison based on the matching of the concepts, which is a fundamental process in the ontologies integration. Each alignment technique uses different strategies; based on specific principles, which make it more adequate for a particular context. This paper proposes an automatic approach for comparison and selection of alignment techniques, given a group of ontologies, based on the ABC algorithm, which is inspire by bee colonies. The approach uses as comparison and selection criteria the execution time, the number of aligned concepts, and the number of times the colony chooses each technique (this is due to the stochastic approach of the ABC algorithm).
机译：从基于服务的本体挖掘的角度出发，本文是对本体集成领域的研究。具体来说，该工作着重于为用户自动提出本体比对建议。由于当前使用本体作为表示知识的机制的趋势，因此本体挖掘领域（OM）是最近的事，这为探索和提取知识创造了广阔的领域。问题在于现有本体的比较，以便将它们一起使用，即找到它们的语义对等。基于概念的匹配，存在用于本体对齐的不同技术，作为本体比较的一种形式，这是本体集成中的基本过程。每种对齐技术使用不同的策略。基于特定的原则，使其更适合特定的环境。在蜜蜂群体的启发下，本文提出了一种基于ABC算法的自动方法，用于比较和选择比对技术，该方法基于一组本体。该方法使用执行时间，对齐概念的数量以及菌落选择每种技术的次数作为比较和选择标准（这是由于ABC算法的随机方法造成的）。

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