Machine assisted learning of entities

Published in Google Patents, 2019

Recommended citation: Elkholy, Alexander Hussam, Balasubramanian Kandaswamy, Steven Matt Gustafson, and Hussein S. Al-Olimat. Machine assisted learning of entities. U.S. Patent Application 10/242,320, filed March 26, 2019.

A data model is traversed to determine concept characteristics associated with concepts that may be associated with entities. Associated documents may be evaluated to identify document characteristics associated with the entities. Entity models may be trained based on the concept characteristics and the document characteristics with each entity model being associated with a confidence value. Results for one or more queries based on the documents and the entity models may be provided. The results may reference the documents that may be associated with the entities. Some entity models may produce results that have a confidence value below a threshold value. Accordingly, the entity models that provide low confidence results may be re-trained.

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