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The Cartographer
xEM: Explainable Entity Matching in Customer 360
December 01, 2022 Β· Declared Dead Β· π COMAD/CODS
"No code URL or promise found in abstract"
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Authors
Sukriti Jaitly, Deepa Mariam George, Balaji Ganesan, Muhammad Ameen, Srinivas Pusapati
arXiv ID
2212.00342
Category
cs.AI: Artificial Intelligence
Citations
0
Venue
COMAD/CODS
Last Checked
5 months ago
Abstract
Entity matching in Customer 360 is the task of determining if multiple records represent the same real world entity. Entities are typically people, organizations, locations, and events represented as attributed nodes in a graph, though they can also be represented as records in relational data. While probabilistic matching engines and artificial neural network models exist for this task, explaining entity matching has received less attention. In this demo, we present our Explainable Entity Matching (xEM) system and discuss the different AI/ML considerations that went into its implementation.
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