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:
Dec. 09, 2025

Filed:

Aug. 22, 2024
Applicant:

Amazon Technologies, Inc., Seattle, WA (US);

Inventors:

Sudheer Babu Tubati, Seattle, WA (US);

Amit Goyal, San Francisco, CA (US);

Rohan Gurappagouda Patil, Mill Creek, WA (US);

Assignee:

Amazon Technologies, Inc., Seattle, WA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04N 21/24 (2011.01); G06F 18/23213 (2023.01); G06N 20/00 (2019.01); G06Q 30/018 (2023.01);
U.S. Cl.
CPC ...
H04N 21/2407 (2013.01); G06F 18/23213 (2023.01); G06N 20/00 (2019.01); G06Q 30/0185 (2013.01);
Abstract

Systems and techniques are disclosed for detecting fraudulent activity by users of a media service, such as a music or video streaming service. Fraudulent activity may artificially modify metrics tracked by the media service, thus impacting chart positions, media recommendations, royalty amounts, and other elements determined by the media service. Media usage data associated with user activity samples is labeled to identify fraud samples and non-fraud samples. Because the majority of user activity on the media service may be legitimate such a number of labeled non-fraud samples exceeds a number of labeled fraud samples, a balanced training data set is created via undersampling to reduce the number of non-fraud samples to be equal or closer to the number of fraud samples. The balanced training data set is used to train a machine learning model to generate fraud predictions associated with new user activity on the media service.


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