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A faster and less aggressive algorithm for correcting conservativity violations in ontology alignments

机译：一种更快，更不具有侵略性的算法，用于校正本体对齐中保守性违规行为

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摘要

Ontologies are computational artifacts that model consensual aspects of reality. In distributed contexts, applications often need to utilize information from several distinct ontologies. In order to integrate multiple ontologies, entities modeled in each ontology must be matched through an ontology alignment. However, imperfect alignments may introduce inconsistencies. One kind of inconsistency, which is often introduced, is the violation of the conservativity principle, that states that the alignment should not introduce new subsumption relations between entities from the same source ontology. We propose a two-step quadratic-time algorithm for automatically correcting such violations, and evaluate it against datasets from the Ontology Alignment Evaluation Initiative 2019, comparing the results to a state-of-the-art approach. The proposed algorithm was significantly faster and less aggressive; that is, it performed fewer modifications over the original alignment when compared to the state-of-the-art algorithm.
机译：本体是计算工件的计算伪影，其现实的同意方面。在分布式上下文中，应用程序通常需要利用来自多个不同的本体的信息。为了集成多个本体，必须通过本体对齐方式匹配在每个本体中建模的实体。但是，不完美的对准可能会引入不一致。通常介绍的一种不一致，是违反了保守原则，使得对齐不应引入来自同一源本体的实体之间的新增资质关系。我们提出了一种两步的二次时间算法，用于自动纠正此类违规行为，并从本体对齐评估计划2019年评估数据集，将结果与最先进的方法进行比较。所提出的算法显着更快，侵略性较小;也就是说，与最先进的算法相比，它在原始对准时执行较少的修改。

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