The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 20, 2024

Filed:

Oct. 29, 2019
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Kelvin Kakugwa, San Francisco, CA (US);

Joe Latone, San Francisco, CA (US);

Nirmit V Desai, Yorktown Heights, NY (US);

Shahrokh Daijavad, Morgan Hill, CA (US);

Wendy Chong, Carmel, NY (US);

Heather D Achilles, Gilmanton, NH (US);

Dinesh C Verma, New Castle, NY (US);

Bijan Davari, Mahapac, NY (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 30/00 (2023.01); G06Q 30/0204 (2023.01); H04L 9/40 (2022.01); G06F 16/9535 (2019.01); G06Q 30/0601 (2023.01); G06N 3/02 (2006.01); G06F 18/214 (2023.01);
U.S. Cl.
CPC ...
G06Q 30/0204 (2013.01); G06F 16/9535 (2019.01); G06F 18/214 (2023.01); G06N 3/02 (2013.01); G06Q 30/0631 (2013.01); H04L 63/0407 (2013.01); H04L 2463/102 (2013.01);
Abstract

Personalization with on-device privacy preservation is provided by receiving, at a user device, a generalized recommendation from a remote provider backend, which include a plurality of candidate items responsive to a request from an application running on the user device; generating a plurality of candidate vectors corresponding to the plurality of candidate items representing a corresponding candidate item in a binary format across a plurality of metrics associated with the plurality of candidate items; generating a user vector based on personal data stored on the user device, the user vector representing a user in a binary format across one or more metrics associated with the personal data; determining interaction propensities based on the user vector and the plurality of candidate vectors according to a global model run on the user device; and displaying, on the user device, the plurality of candidate items according to the interaction propensities.


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