Patent ID: 11914844
Assignee: TRUIST BANK
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 17:
18. A method for training a neural network that performs filtering and display of content data comprising the operations of:
(a) processing content data by a content aggregation and reduction service by performing an interrogative analysis utilizing one or more neural networks, wherein
(i) each neural network has at least one hidden layer,
(ii) the at least one hidden layer comprises a plurality of nodes with each node comprising at least one weighting coefficient, and wherein
(iii) the interrogative analysis generates a first interrogative data set comprising one or more interrogatories, source identifier data for each of the interrogatories, and source weighting data for each source identifier,

(b) processing the content data by the content aggregation and reduction service by performing a subject classification analysis utilizing the one or more neural networks, wherein the subject classification analysis generates a first subject classification data set comprising (i) subject identifier data, and (ii) subject weighting data for each subject identifier;
(c) performing a labelling analysis on the received content data to generate (i) annotated interrogative data comprising one or more known interrogatories, a known source identifier for each of the known interrogatories, and known source weighting data for each source identifier, and (ii) annotated subject classification data comprising known subject identifier data and known subject weighting data for each subject identifier;
(d) generating an interrogative error data and subject classification error data, by performing operations comprising
(i) applying the first interrogative data set against the annotated interrogative data to generate the interrogative error data, and
(ii) applying the first subject classification data set against the annotated subject classification data to generate the subject classification error data;

(e) refining the one or more neural networks by performing operations comprising
(i) feeding the interrogative error data and the subject classification error data through the one or more neural networks, and
(ii) adjusting the weighting coefficients to minimize the interrogative error data and the subject classification error data.