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. 16, 2023

Filed:

Sep. 29, 2017
Applicant:

Salesforce.com, Inc., San Francisco, CA (US);

Inventors:

Scott Thurston Rickard, Jr., Bellevue, WA (US);

Elizabeth Rachel Balsam, San Francisco, CA (US);

Tracy Morgan Backes, Seattle, WA (US);

Zachary Alexander, Snoqualmie, WA (US);

Assignee:

Salesforce, Inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 30/02 (2012.01); G06N 20/10 (2019.01); G06N 5/022 (2023.01); G06N 20/00 (2019.01); G06N 5/00 (2023.01); G06N 20/20 (2019.01); G06Q 30/0201 (2023.01); G06Q 30/0203 (2023.01); G06Q 30/0204 (2023.01); G06N 3/08 (2023.01); G06N 7/00 (2023.01);
U.S. Cl.
CPC ...
G06N 5/022 (2013.01); G06N 5/003 (2013.01); G06N 20/00 (2019.01); G06N 20/20 (2019.01); G06Q 30/0201 (2013.01); G06Q 30/0203 (2013.01); G06Q 30/0204 (2013.01); G06N 3/08 (2013.01); G06N 7/005 (2013.01); G06N 20/10 (2019.01);
Abstract

An online system stores objects representing potential transactions of an enterprise. The online system uses predictor models to determine an aggregate score based on values of the objects associated with a time interval, for example, a month. Each object is configured to take one of a plurality of states. The online system stores historical data describing activities associated with potential transaction objects and uses the stored data for generating the predictor models. The online system categorizes the objects into bins based on states of the objects. The online system may generate different predictions for each category. The online system may use machine learning based models as predictor models. The online system extracts features describing potential transaction objects and provides these as input to the predictor model.


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