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:
Jan. 04, 2022

Filed:

Apr. 28, 2017
Applicant:

Cisco Technology, Inc., San Jose, CA (US);

Inventors:

Kabiraj Sethi, Fremont, CA (US);

Ajith Chandran, San Jose, CA (US);

Amitesh Shukla, Milpitas, CA (US);

Assignee:

Cisco Technology, Inc., San Jose, CA (US);

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); G06Q 10/00 (2012.01); G06N 5/02 (2006.01); G06Q 10/10 (2012.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06N 5/02 (2013.01); G06Q 10/00 (2013.01); G06Q 10/10 (2013.01); G06Q 10/20 (2013.01);
Abstract

In one embodiment, a machine learning server in a computer network determines a plurality of computing features shared across a given set of computing products, and collects, from each computing product of the given set, problem-solution data for each computing feature of the plurality of computing features. Problem-solution data is indicative of problems related to a respective computing feature, attempted solution actions for the problems, and outcomes of the attempted solutions on the problem. The machine learning server updates a machine learning model of suggested solutions for computing-feature-specific problems based on the collected problem-solution data, and provides, based on the machine learning model, a particular suggested solution for a particular computing-feature-specific problem to a particular computing product. An outcome of the particular suggested solution for the particular computing-feature-specific problem on the particular computing product may then be fed back to the machine learning server as collected problem-solution data.


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