US 11,868,886 B2
Time-preserving embeddings
Jelena Gligorijevic, San Jose, CA (US); Ivan Stojkovic, San Jose, CA (US); Martin Pavlovski, Philadelphia, PA (US); Shubham Agrawal, San Jose, CA (US); Djordje Gligorijevic, San Jose, CA (US); Srinath Ravindran, Santa Clara, CA (US); Richard Hin-Fai Tang, Saratoga, CA (US); Shabhareesh Komirishetty, Sunnyvale, CA (US); Chander Jayaraman Iyer, Santa Clara, CA (US); and Lakshmi Narayan Bhamidipati, Sunnyvale, CA (US)
Assigned to Yahoo Assets LLC, New York, NY (US)
Filed by Verizon Media Inc., New York, NY (US)
Filed on Jan. 25, 2021, as Appl. No. 17/157,071.
Prior Publication US 2022/0237442 A1, Jul. 28, 2022
Int. Cl. G06N 3/08 (2023.01); G06F 11/34 (2006.01); G06F 16/955 (2019.01); G06F 18/22 (2023.01); G06F 18/214 (2023.01); G06F 18/2413 (2023.01); G06N 3/048 (2023.01)
CPC G06N 3/08 (2013.01) [G06F 11/3438 (2013.01); G06F 16/9566 (2019.01); G06F 18/214 (2023.01); G06F 18/22 (2023.01); G06F 18/24147 (2023.01); G06N 3/048 (2023.01); G06F 2201/835 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
executing, on a processor of a computing device, instructions that cause the computing device to perform operations, the operations comprising:
generating user trails of activities performed by users;
identifying frequencies at which the activities were performed;
assigning indices to a set of activities identified from the activities as having frequencies above a threshold, wherein the assigning comprises assigning a first index to a first activity having a first frequency above the threshold and assigning a second index to a second activity having a second frequency above the threshold;
mapping activity descriptions of the set of activities to the indices to generate a vocabulary, wherein the mapping comprises mapping a first activity description to the first index assigned to the first activity and mapping a second activity description to the second index assigned to the second activity; and
training a model using the user trails, timestamps of the activities, and the vocabulary to learn a set of time-preserving embeddings.