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Structural Alignment Methods with Applications to Geospatial Ontologies

机译:结构对齐方法及其在地理空间本体中的应用

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摘要

We consider the problem of enabling interoperability and information sharing among geospatial applications that use ontologies to describe their concepts and the relationships among them. We present two fully automatic alignment methods that use the graph structures of a pair of ontologies to establish their alignment, that is, the semantic correspondences between their concepts. We have tested our methods on geospatial ontologies pertaining to wetlands and four other pairs that belong to a repository that has been used in the Ontology Alignment Evaluation Initiative (OAEI). Using these ontologies, we have compared the effectiveness (precision and recall) of our methods against the Similarity Flooding Algorithm that was proposed by others and show that for each of the tested ontologies one of our methods is at least as effective as their method. We have tuned the performance of our methods by introducing a greedy approach that reduces the number of concepts that get compared. This approach reduces runtime by approximately 30% with a minor compromise to the effectiveness of the results. To further validate our approach, we participated in the OAEI competition to align a pair of ontologies, each with a few thousand concepts.
机译:我们考虑在使用本体描述其概念及​​其之间关系的地理空间应用程序之间实现互操作性和信息共享的问题。我们提出了两种全自动对齐方式,它们使用一对本体的图结构来建立对齐方式,即它们概念之间的语义对应。我们已经测试了关于湿地和其他四个对的地理空间本体的方法,这些对属于一个存储库,该存储库已在本体一致性评估计划(OAEI)中使用。使用这些本体,我们已经将我们的方法的有效性(精确度和召回率)与其他人提出的相似性泛洪算法进行了比较,并表明对于每种经过测试的本体,我们的一种方法至少与它们的方法一样有效。我们通过引入贪婪的方法来减少所比较概念的数量,从而调整了方法的性能。这种方法将运行时间减少了大约30%,同时对结果的有效性略有妥协。为了进一步验证我们的方法,我们参加了OAEI竞赛,以使一对本体一致,每个本体都有数千个概念。

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