Exploiting Transitivity Constraints for Entity Matching in Knowledge Graphs

• URL: http://arxiv.org/abs/2104.12589v1
• Date: Thu, 22 Apr 2021 10:57:01 GMT
• Title: Exploiting Transitivity Constraints for Entity Matching in Knowledge Graphs
• Authors: Jurian Baas, Mehdi Dastani, Ad Feelders
• Abstract summary: We show that an ad-hoc enforcement of transitivity on identified set of entity pairs may decrease precision dramatically. We propose a methodology that starts with a given similarity measure, generates a set of entity pairs that are identified as referring to the same real-world objects, and applies the cluster editing algorithm to enforce transitivity without adding many spurious links.
• Score: 1.7080853582489066
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: The goal of entity matching in knowledge graphs is to identify entities that refer to the same real-world objects using some similarity metric. The result of entity matching can be seen as a set of entity pairs interpreted as the same-as relation. However, the identified set of pairs may fail to satisfy some structural properties, in particular transitivity, that are expected from the same-as relation. In this work, we show that an ad-hoc enforcement of transitivity, i.e. taking the transitive closure, on the identified set of entity pairs may decrease precision dramatically. We therefore propose a methodology that starts with a given similarity measure, generates a set of entity pairs that are identified as referring to the same real-world objects, and applies the cluster editing algorithm to enforce transitivity without adding many spurious links, leading to overall improved performance.

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