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Entity matching in Customer 360 is the task of determining if multiplerecords represent the same real world entity. Entities are typically people,organizations, locations, and events represented as attributed nodes in agraph, though they can also be represented as records in relational data. Whileprobabilistic matching engines and artificial neural network models exist forthis task, explaining entity matching has received less attention. In thisdemo, we present our Explainable Entity Matching (xEM) system and discuss thedifferent AI/ML considerations that went into its implementation.

xEM: Explainable Entity Matching in Customer 360