Patent ID: 11893351
Assignee: INTUIT INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 7:
8. A method of training a machine learning model, comprising:
receiving a corpus comprising a plurality of natural language words, wherein the plurality of natural language words are organized into a plurality of known key phrases;
inputting at least part of the corpus as a vector into the machine learning model, wherein the machine learning model comprises a plurality of layers and a retrospective layer,
determining, using the plurality of layers, a probability that a first word in the corpus is a first keyword in at least one of a plurality of predicted key phrases,
determining, using the retrospective layer, a first modified probability that the first word is the first keyword based on a first position of the first word relative to a second position of a second word in the corpus,
wherein the first modified probability punishes the first word when the first word depends on the second word and the second word comes after the first word, and
wherein punishes comprises reducing a probability that the first word is in the predicted key phrases;

determining, using the machine learning model, the plurality of predicted key phrases, wherein at least one of the plurality of predicted key phrases comprises at least the first word;
calculating a loss function by comparing and evaluating a difference between the plurality of predicted key phrases and the plurality of known key phrases; and
modifying the machine learning model using the loss function.