Metadata aggregation using a trained entity matching predictive model

• Main Authors: Farre Guiu, Miquel Angel, Pujol, Jordi Badia, Lawson, Calvin, Martin, Marc Junyent, Stoafer, Christopher C, Bravo, Francesc Josep Guitart, Luerken, Erick L
• Format: Patent
• Language: English
• Published: 26.04.2022
• Subjects: CALCULATING; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS

A metadata aggregation system includes a computing platform having a hardware processor and a memory storing a software code including a trained entity matching predictive model trained using training data obtained from a reference database. The hardware processor executes the software code to obtain metadata inputs from multiple sources, conform the metadata inputs to a common format, match, using the trained entity matching predictive model, at least some of the conformed metadata inputs to the same entity, and determine, using the trained entity matching predictive model, a confidence score for each match. The software code further sends a request to one or more human editor(s) for confirmation of each match having a confidence score greater than a first threshold and less than a second threshold, and updates the reference database, in response to receiving a confirmation that at least one match is a confirmed match, to include the confirmed match.