TRAINING MACHINE LEARNING MODELS FOR MULTI-MODAL ENTITY MATCHING IN ELECTRONIC RECORDS

A cloud platform trains a machine-learned entity matching model that generates predictions on whether a pair of electronic records refer to a same entity. In one embodiment, the entity matching model is configured as a transformer architecture. In one instance, the entity matching model is trained u...

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Bibliographische Detailangaben
Hauptverfasser: Singh, Akash, Jagota, Arun Kumar, Dua, Rajdeep
Format: Patent
Sprache:eng
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Beschreibung
Zusammenfassung:A cloud platform trains a machine-learned entity matching model that generates predictions on whether a pair of electronic records refer to a same entity. In one embodiment, the entity matching model is configured as a transformer architecture. In one instance, the entity matching model is trained using a combination of a first loss and a second loss. The first loss indicates a difference between an entity matching prediction for a training instance and a respective match label for the training instance. The second loss indicates a difference between a set of named-entity recognition (NER) predictions for the training instance and the set of NER labels for the tokens of the training instance.