Ontology matching aims at discovering mappings between the entities of two ontologies. It plays an important role in the integration of heterogeneous data sources that are described by ontologies. Interactive ontology matching involves domain experts in the matching process. In some approaches, the expert provides feedback about mappings between ontology entities, that is, these approaches select mappings to present to the expert who replies which of them should be accepted or rejected, so taking advantage of the knowledge of domain experts towards finding an alignment. In this paper, we present Alin, an interactive ontology matching approach which uses expert feedback not only to approve or reject selected mappings but also to dynamically improve the set of selected mappings, that is, to interactively include and to exclude mappings from it. This additional use for expert answers aims at increasing in the benefit brought by each expert answer. For this purpose, Alin uses four techniques. Two techniques were used in the previous versions of Alin to dynamically select concept and attribute mappings. Two new techniques are introduced in this paper: one to dynamically select relationship mappings and another one to dynamically reject inconsistent selected mappings using anti-patterns. We compared Alin with state-of-the-art tools, showing that it generates alignment of comparable quality.

中文翻译：

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Alin：通过交互式修改映射建议来改进交互式本体匹配

本体匹配旨在发现两个本体的实体之间的映射。它在本体描述的异构数据源的集成中发挥着重要作用。交互式本体匹配涉及匹配过程中的领域专家。在一些方法中，专家提供关于本体实体之间映射的反馈，也就是说，这些方法选择映射呈现给专家，专家回答应该接受或拒绝其中的哪些，因此利用领域专家的知识来找到对齐. 在本文中，我们提出阿林，一种交互式本体匹配方法，它不仅使用专家反馈来批准或拒绝选定的映射，而且还动态地改进选定映射的集合，即交互式地包含和排除映射。专家答案的这种额外用途旨在增加每个专家答案带来的好处。以此目的，阿林使用四种技术。在之前的版本中使用了两种技术阿林动态选择概念和属性映射。本文介绍了两种新技术：一种是动态选择关系映射，另一种是使用反模式动态拒绝不一致的选择映射。我们比较了阿林使用最先进的工具，表明它产生了可比质量的对齐。