US Patent 11875253 Low-resource entity resolution with transfer learning

Methods, systems, and computer program products for low-resource entity resolution with transfer learning are provided herein. A computer-implemented method includes processing input data via a first entity resolution model, wherein the input data comprise labeled input data and unlabeled input data; identifying one or more portions of the unlabeled input data to be used in training a neural network entity resolution model, wherein said identifying comprises applying one or more active learning algorithms to the first entity resolution model; training, using (i) the one or more portions of the unlabeled input data and (ii) one or more deep learning techniques, the neural network entity resolution model; and performing one or more entity resolution tasks by applying the trained neural network entity resolution model to one or more datasets.