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:
Jun. 07, 2022

Filed:

Sep. 24, 2019
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Jignashu Parikh, San Jose, CA (US);

Subhadip Sarkar, San Jose, CA (US);

Assignee:

GOOGLE LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/95 (2019.01); G06F 16/9537 (2019.01); G06F 16/9535 (2019.01); B32B 5/10 (2006.01); B32B 27/06 (2006.01); B32B 27/38 (2006.01); C08J 5/10 (2006.01); C08J 5/12 (2006.01); C08J 5/24 (2006.01); C08K 5/5317 (2006.01); C08L 63/00 (2006.01); H05K 1/03 (2006.01); H05K 3/46 (2006.01); C08K 5/00 (2006.01);
U.S. Cl.
CPC ...
G06F 16/9537 (2019.01); B32B 5/10 (2013.01); B32B 27/06 (2013.01); B32B 27/38 (2013.01); C08J 5/10 (2013.01); C08J 5/124 (2013.01); C08J 5/24 (2013.01); C08K 5/5317 (2013.01); C08L 63/00 (2013.01); G06F 16/9535 (2019.01); H05K 1/0373 (2013.01); H05K 3/4626 (2013.01); B32B 2262/101 (2013.01); B32B 2307/3065 (2013.01); B32B 2363/00 (2013.01); B32B 2457/00 (2013.01); B32B 2457/08 (2013.01); C08J 2363/00 (2013.01); C08J 2463/00 (2013.01); C08K 5/0066 (2013.01); C08L 2201/02 (2013.01); C08L 2203/20 (2013.01); H05K 2201/012 (2013.01); H05K 2203/1147 (2013.01);
Abstract

Methods and systems for providing a user with content relevant to a location of interest to the user, when the user is determined to be at or near the location, are presented. The user's interest in the location may be determined based on queries about the location received from the user prior to the user arriving at the location. The queries received from the user about the location are used to build a location recommendation model, which generates personalized content relevant to the location and to one or more interest verticals identified for the user. The location recommendation model is built using a location recommendation engine that collects data about the user, the queried location, one or more associations between the user, the queried location, and/or one or more other users, as well as various other information related to the user's interests and the queried location.


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