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In particular, Landmark Explanation computes local interpretations, i.e., given a description of a pair of entities and an EM model, it computes the contribution of each term in generating the prediction.
Oct 30, 2021
Machine Learning (ML) and Deep Learning (DL) models have been successfully applied to the. Entity Matching (EM) problem as the state-of-the-art approaches ...
Entity Matching specific Explanation tool. Landmark generates reliable and coherent explanations through a perturbation analysis.
of interpretability of their behavior. This paper showcases Landmark Explanation. 1. , a tool that makes. generic post-hoc (model-agnostic) perturbation-based ...
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This tool is designed to deal with the specific characteristics of the Entity matching problem that involve a comparison between two textual descriptions which ...
2019. TLDR. This work proposes ExplainER, a tool to understand and explain entity resolution classifiers with different granularity levels of explanations ...
matching record explanations. 5 CONCLUSION. This paper introduces Landmark Explanation a tool that makes a post-hoc perturbation-based explainer able to deal ...
We introduce Landmark Explanation, a framework that extends the capabilities of a post-hoc perturbationbased explainer to the EM scenario. Landmark Explanation ...
... /paper8⫸Vol-3194/paper9. Andrea Baraldi 0002 Francesco Del Buono Matteo Paganelli Francesco Guerra 0001. Landmark Explanation: a Tool for Entity Matching.
This paper showcases Landmark Explanation1, a tool that makes generic post-hoc (model-agnostic) perturbation-based explanation systems able to explain the ...