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:
Sep. 24, 2019

Filed:

Oct. 26, 2017
Applicant:

Hrl Laboratories, Llc, Malibu, CA (US);

Inventor:

Hankyu Moon, Oak Park, CA (US);

Assignee:

HRL Laboratories, LLC, Malibu, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 17/16 (2006.01); G06F 17/00 (2019.01); G06F 16/335 (2019.01); G06N 20/00 (2019.01); G06F 16/35 (2019.01); G06F 16/33 (2019.01);
U.S. Cl.
CPC ...
G06F 16/337 (2019.01); G06F 16/3346 (2019.01); G06F 16/35 (2019.01); G06F 17/16 (2013.01); G06N 20/00 (2019.01);
Abstract

Described is a system for identifying predictive keywords and generating a forecast. The system receives time-series of keyword counts (the time-series of keyword counts having a plurality of candidate keywords). The time-series of keyword counts are separated (i.e., marked or designated) into a group of time-series from active periods and a group of time-series from inactive periods. A covariance matrix is generated for each group of time-series. Generalized eigenvectors are generated between the two covariance matrices. Candidate keywords are ranked based on the generalized eigenvectors, such that candidate keywords having a rank exceeding a predetermined threshold are designated as predictive keywords. The predictive keywords are then provided to a machine learning system that generates a forecast based on the predictive keywords. Finally, a device is operated based on the forecast.


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