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:
May. 04, 2021

Filed:

Aug. 21, 2018
Applicant:

Adobe Inc., San Jose, CA (US);

Inventors:

Charles Menguy, New York, NY (US);

Sudhakar Pandey, Noida, IN;

Roshan Singh, Greater Noida West, IN;

Ravi Prakash Singh, Noida, IN;

David Meier Weinstein, Rockville Centre, NY (US);

Ankush Sharma, Noida, IN;

Assignee:

Adobe Inc., San Jose, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 17/20 (2006.01); G06F 16/957 (2019.01); H04L 29/08 (2006.01); G06F 16/31 (2019.01); G06F 16/9535 (2019.01); G06F 16/955 (2019.01);
U.S. Cl.
CPC ...
G06F 16/9577 (2019.01); G06F 16/313 (2019.01); G06F 16/9535 (2019.01); G06F 16/9566 (2019.01); H04L 67/22 (2013.01);
Abstract

Systems and techniques for delivery of contextual interest from interaction information are described that process user interactions with digital content to generate user interest scores for various topics. A contextual user interest system uses user interaction data to identify and contextualize content, and assigns propensity scores to the contextualized content. By dynamically contextualizing pages of content, the contextual user interest system may adapt to changes in the content and provide more accurate and robust information over time, which is not possible using conventional techniques. The contextualized pages of content are used to assign user interest scores across a number of topics to users who have visited the pages of content, and the user interest scores are normalized in a manner that allows a user's degree of interest in a topic to be compared to that of another user.


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