CPC G06V 30/414 (2022.01) [G06F 18/214 (2023.01); G06F 18/2413 (2023.01); G06F 40/284 (2020.01); G06N 3/08 (2013.01); G06V 30/416 (2022.01)] | 18 Claims |
1. A method, comprising:
generating machine-learning models configured to identify a document as in class or out of class, the machine-learning models trained utilizing user input data indicating a first portion of documents as in class and a second portion of documents as out of class, wherein the documents are intellectual property documents;
determining, for individual ones of the machine-learning models, a category associated with individual ones of the machine-learning models, the category associated with a classification system associated with the documents;
generating a taxonomy of the machine-learning models, the taxonomy indicating categorical relationships between the machine-learning models, wherein generating the taxonomy is based at least in part on the category associated with the individual ones of the machine-learning models;
receiving, for a machine-learning model of the machine-learning models, a training dataset configured to train the machine-learning model to determine which of the documents are in class to the machine-learning model;
receiving an indication that a portion of the training dataset includes confidential information;
generating a modified machine-learning model corresponding to the machine-learning model trained without the portion of the training dataset that includes the confidential information; and
wherein generating the taxonomy comprises generating the taxonomy based at least in part on the modified machine-learning model.
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