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. 28, 2020

Filed:

Aug. 27, 2018
Applicant:

Ayasdi Ai Llc, Menlo Park, CA (US);

Inventors:

Pek Yee Lum, Palo Alto, CA (US);

Eithon Cadag, Foster City, CA (US);

Johan Grahnen, Palo Alto, CA (US);

Joshua Lewis, San Francisco, CA (US);

Harlan Sexton, Palo Alto, CA (US);

Assignee:

Ayasdi AI LLC, Menlo Park, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/28 (2019.01); G06F 16/955 (2019.01); G16H 10/60 (2018.01); G16H 50/70 (2018.01); G16H 50/20 (2018.01);
U.S. Cl.
CPC ...
G06F 16/285 (2019.01); G06F 16/955 (2019.01); G16H 10/60 (2018.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01);
Abstract

An example method comprises receiving historical information of episodes, constructing event sets from the historical information, categorizing each event with general labels and synthetic labels, learning an event metric on the events by using the general and synthetic labels to perform dimensionality reduction to associate a vector with each event and to determine an angle between every two vectors, determining an event set metric using distances between each pair of event sets, deriving a sequence metric on the episodes, the sequence metric obtaining a preferred match between two episodes, deriving a subsequence metric on the episodes, the subsequence metric is a function of the event set metric on subsequences of each episode, grouping episodes into subgroups based on distances, for at least one subgroup, generating a consensus sequence by finding a preferred sequence of events, and the episodes of the subgroup, and generating a report indicating the consensus sequence.


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