Patent ID: 11880411
Assignee: HOME DEPOT PRODUCT AUTHORITY, LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 16:
17. A method for training a machine learning algorithm to create a trained model, the trained model for recognizing one or more named entities in a user search query, the one or more named entities having one or more entity types, the method comprising:
defining a first data set according to user behavior data, the first data set comprising a plurality of first data pairs, each first data pair comprising a user search query and one or more defined named entity values in the user search query;
determining a plurality of named entity values in the user search queries of the first data set that are not in the associated defined named entity values of the first data set;
adding the determined plurality of named entity values to the defined named entity values of the first data set to create a supplemented first data set;
defining a second data set by creating a plurality of artificial second data pairs, each second data pair comprising an artificial search query and one or more defined named entity values in the artificial search query;
training the machine learning algorithm to create a trained model by:
(i) defining an initial training data set comprising a portion of the supplemented first training data set;
(ii) training the algorithm according to the supplemented first training data set;
(iii) adding further data from the supplemented first training data set and from the second data set to the initial training data set to create a further training data set;
(iv) training the algorithm according to the further training data set; and
(v) iteratively repeating (iii) and (iv) until an accuracy of the trained model exceeds a predetermined threshold or until a predetermined number of iterations has been performed.