US 11,868,228 B2
Content item selection and click probability determination based upon accidental click events
Naama Haramaty-Krasne, Hapekan (IL); Yohay Kaplan, Haifa (IL); Oren Shlomo Somekh, Kfar-Neter (IL); and Alexander Shtoff, Haifa (IL)
Assigned to Yahoo Ad Tech LLC, New York, NY (US)
Filed by Yahoo Ad Tech LLC, Dulles, VA (US)
Filed on Jan. 19, 2023, as Appl. No. 18/098,734.
Application 18/098,734 is a continuation of application No. 17/346,339, filed on Jun. 14, 2021, granted, now 11,561,879.
Prior Publication US 2023/0153221 A1, May 18, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 11/34 (2006.01); G06N 20/00 (2019.01); G06F 16/95 (2019.01); G06F 3/04842 (2022.01)
CPC G06F 11/3438 (2013.01) [G06F 3/04842 (2013.01); G06F 16/95 (2019.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
identifying a first plurality of sets of event information associated with a first plurality of events, wherein the first plurality of sets of event information comprises:
a second plurality of sets of event information associated with a plurality of accidental click events of the first plurality of events; and
a third plurality of sets of event information associated with a plurality of skip events of the first plurality of events;
determining a plurality of accidental click probabilities associated with a second plurality of events comprising the plurality of accidental click events and the plurality of skip events, wherein the determining the plurality of accidental click probabilities comprises:
determining a first accidental click probability, associated with a first accidental click event of the plurality of accidental click events, based upon a first set of event information associated with the first accidental click event; and
determining a second accidental click probability, associated with a first skip event of the plurality of skip events, based upon a second set of event information associated with the first skip event;
performing machine learning model training, using the first plurality of sets of event information associated with the first plurality of events and a first plurality of labels associated with the first plurality of events, to generate a first machine learning model, wherein:
the first plurality of labels comprises a second plurality of labels associated with the second plurality of events; and
labels of the second plurality of labels are based upon the plurality of accidental click probabilities and comprise:
a first label, associated with the first accidental click event, based upon the first accidental click probability; and
a second label, associated with the first skip event, based upon the second accidental click probability;
receiving a request for content associated with a client device;
responsive to receiving the request for content, determining a plurality of click probabilities associated with a plurality of content items using the first machine learning model; and
selecting, based upon the plurality of click probabilities, a first content item of the plurality of content items for presentation via the client device.