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:
Jul. 02, 2024

Filed:

Oct. 15, 2020
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Matthew Sharifi, Kilchberg, CH;

Daniel Ramage, Seattle, WA (US);

David Petrou, Brooklyn, NY (US);

Assignee:

GOOGLE LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 3/0481 (2022.01); G06F 3/0482 (2013.01); G06F 3/0484 (2022.01); G06F 3/04895 (2022.01); G06F 9/451 (2018.01); G06F 16/245 (2019.01); G06F 16/332 (2019.01); G06N 5/02 (2023.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 3/0481 (2013.01); G06F 3/0482 (2013.01); G06F 3/0484 (2013.01); G06F 3/04895 (2013.01); G06F 9/453 (2018.02); G06F 16/245 (2019.01); G06F 16/3322 (2019.01); G06N 5/02 (2013.01);
Abstract

Systems and methods are provided for suggesting actions for selected text based on content displayed on a mobile device. An example method can include converting a selection made via a display device into a query, providing the query to an action suggestion model that is trained to predict an action given a query, each action being associated with a mobile application, receiving one or more predicted actions, and initiating display of the one or more predicted actions on the display device. Another example method can include identifying, from search records, queries where a website is highly ranked, the website being one of a plurality of websites in a mapping of websites to mobile applications. The method can also include generating positive training examples for an action suggestion model from the identified queries, and training the action suggestion model using the positive training examples.


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