Patent ID: 11893065
Assignee: AON RISK SERVICES, INC. OF MARYLAND
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 12:
13. A system comprising:
one or more processors; and
non-transitory computer-readable media storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
storing a taxonomy of machine-learning models trained to predict a classification of documents in a document set utilizing predictive analytical techniques, individual ones of the machine-learning models trained based at least in part on a document dataset indicated to be in class at least in part from first user input data, wherein the individual ones of the machine-learning models differ from the documents that the models are configured to receive and analyze;
generating a user interface configured to accept second user input data representing a search query, the search query including keywords from the second user input data;
receiving second user input data representing a search query, the search query including keywords from the first user input data;
generating, utilizing the keywords, a first dataset based at least in part on the search query;
determining, utilizing the first dataset, that at least one machine-learning model of the taxonomy of machine-learning models was trained by a second dataset similar to the first dataset;
generating, based at least in part on the determining, a recommended machine-learning classification model of the machine-learning models determined to be most related to the search query; and
based at least in part on the determining, causing display of search results for the search query, the search results displaying a visual representation of the taxonomy along with an emphasized portion of the visual representation associated with the at least one machine-learning classification model of the taxonomy of machine-learning models trained by the second dataset, the search results also indicating the recommended machine-learning classification model.