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. 10, 2023

Filed:

Feb. 18, 2020
Applicant:

Emc Ip Holding Company Llc, Hopkinton, MA (US);

Inventors:

Fangyuan Lin, Chengdu, CN;

Xiaohui Wang, Chengdu, CN;

Hui Li, Chengdu, CN;

Li Yuan, Chengdu, CN;

Assignee:

EMC IP HOLDING COMPANY LLC, Hopkinton, MA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/82 (2022.01); G06N 3/08 (2006.01); G06F 16/17 (2019.01); G06K 9/62 (2022.01); G06N 3/04 (2006.01); G06F 11/10 (2006.01); G06F 21/60 (2013.01); G06V 10/77 (2022.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06F 11/1024 (2013.01); G06F 16/1734 (2019.01); G06F 21/60 (2013.01); G06K 9/6232 (2013.01); G06N 3/04 (2013.01); G06V 10/7715 (2022.01); G06V 10/82 (2022.01);
Abstract

Embodiments of the present disclosure provide a method, device, and computer program product for error evaluation. A method for error evaluation comprises in accordance with a determination that an error occurs in a data protection system, obtaining context information related to an operation of the data protection system; determining, based on the context information and using a trained deep learning model, a type of the error in the data protection system from a plurality of predetermined types, the deep learning model being trained based on training context information and a label on a ground-truth type of an error associated with the training context information; and providing the determined type of the error in the data protection system. In this way, it is possible to achieve automatic classification of errors in the data protection system, thereby improving the efficiency in error classification and saving the operation costs. Therefore, more rapid and more accurate measures can be taken to handle the errors.


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