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. 26, 2023

Filed:

May. 25, 2021
Applicant:

Adobe Inc., San Jose, CA (US);

Inventors:

Atanu Sinha, Bangalore, IN;

Manoj Kilaru, Telangana, IN;

Iftikhar Ahamath Burhanuddin, Bengaluru, IN;

Aneesh Shetty, Navi Mumbai, IN;

Titas Chakraborty, Navi Mumbai, IN;

Rachit Bansal, Sangrur, IN;

Tirupati Saketh Chandra, Andhra Pradesh, IN;

Fan Du, Milpitas, CA (US);

Aurghya Maiti, West Bengal, IN;

Saurabh Mahapatra, Sunnyvale, CA (US);

Assignee:

ADOBE, INC., San Jose, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 10/0639 (2023.01); G06F 18/214 (2023.01); G06F 18/2321 (2023.01);
U.S. Cl.
CPC ...
G06Q 10/06393 (2013.01); G06F 18/214 (2023.01); G06F 18/2321 (2023.01);
Abstract

Systems and methods for data analytics are described. One or more embodiments of the present disclosure receive target time series data and candidate time series data, where the candidate time series data includes data corresponding to each of a plurality of candidate metrics, train a prediction network to predict the target time series data based on the candidate time series data by setting temporal attention weights corresponding to a plurality of rolling time windows and by setting candidate attention weights corresponding to the plurality of candidate metrics, identify a leading indicator metric for the target time series data from the plurality of candidate metrics based on the temporal attention weights and the candidate attention weights, and signal the leading indicator metric for the target time series data.


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