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:
Oct. 15, 2024

Filed:

Jul. 19, 2021
Applicant:

Verizon Patent and Licensing Inc., Basking Ridge, NJ (US);

Inventors:

Yoelle Maarek, Haifa, IL;

Ido Guy, Haifa, IL;

Dan Pelleg, Haifa, IL;

Idan Szpektor, Kfar Saba, IL;

Alexander Nus, Rishon LeZion, IL;

Jeffrey Bonforte, San Francisco, CA (US);

Assignee:

Verizon Patent and Licensing Inc., Basking Ridge, NJ (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04L 51/08 (2022.01); G06F 16/583 (2019.01); G06Q 50/00 (2024.01); G06V 20/30 (2022.01); H04L 51/10 (2022.01);
U.S. Cl.
CPC ...
H04L 51/08 (2013.01); G06F 16/583 (2019.01); G06Q 50/01 (2013.01); G06V 20/30 (2022.01); H04L 51/10 (2013.01);
Abstract

Disclosed are systems and methods for improving interactions with and between computers in content searching, generating, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosure provides a novel, computerized framework for automatically identifying and recommending socially-engaging photos to their creators for sharing. Execution of the disclosed systems and methods turns a tedious manual chore into an automated, software-driven process. The disclosed systems and methods utilizes a novel, computerized learn-to-rank (LTR) algorithm for identifying the most engaging, socially driven photos by: (a) grouping near-duplicate photos; (b) selecting a representative photo for sharing per group; and (c) ranking of the groups by their likelihood to contain a 'shareable' photo.


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