US 12,423,381 B2
Model with usage data compensation
Oren Barkan, Tel-Aviv (IL); Roy Hirsch, Tel Aviv (IL); Ori Katz, Tel-Aviv (IL); Avi Caciularu, Tel-Aviv (IL); Yonathan Weill, Tel-Aviv (IL); Noam Koenigstein, Tel Aviv (IL); and Nir Nice, Salit (IL)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed on Dec. 6, 2021, as Appl. No. 17/543,065.
Prior Publication US 2023/0177111 A1, Jun. 8, 2023
Int. Cl. G06F 18/2115 (2023.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01)
CPC G06F 18/2115 (2023.01) [G06F 18/2148 (2023.01); G06F 18/217 (2023.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method of training a machine learning model, the method comprising:
receiving training data in the machine learning model, the received training data including content data for one or more items accessible to one or more users and input usage data labels representing recorded interaction between each user and each item, wherein the content data for each item includes data representing intrinsic attributes of the item;
generating modified training data by including the content data and the input usage data labels for a second proper subset of items and the input usage data labels for the first proper subset of the items and by excluding the input usage data labels for the first proper subset of the items, the second proper subset of the items corresponding to the items not included in the first proper subset;
simulating, by a usage data simulator of the machine learning model and for the first proper subset of items, simulated usage data labels, based on the content data for the first proper subset of the items;
adding the simulated usage data labels to the modified training data; and
training the machine learning model using the modified training data to predict input usage data of an input item based on input content data of the input item.