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:
Aug. 10, 2021

Filed:

Dec. 19, 2018
Applicant:

Netskope, Inc., Santa Clara, CA (US);

Inventors:

Sandeep Yadav, South San Francisco, CA (US);

Ravindra K. Balupari, San Jose, CA (US);

Assignee:

Netskope, Inc., Santa Clara, CA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/31 (2019.01); G06F 16/35 (2019.01); G06K 9/62 (2006.01); G06N 20/10 (2019.01); G06F 16/951 (2019.01);
U.S. Cl.
CPC ...
G06K 9/6269 (2013.01); G06F 16/313 (2019.01); G06F 16/35 (2019.01); G06F 16/951 (2019.01); G06N 20/10 (2019.01);
Abstract

The technology disclosed includes a system to perform multi-label support vector machine (SVM) classification of a document. The system creates document features representing frequencies or semantics of words in the document. Trained SVM classification parameters for a plurality of labels are applied to the document features for the document. The system determines positive and negative distances between SVM hyperplanes for the labels and the feature vector. Labels with positive distance to the feature vector are harvested. When the distribution of negative distances is characterized by a mean and standard deviation, the system further harvests the labels with a negative distance such that the harvested labels include the labels with a negative distance between the mean negative distance and zero and separated from the mean negative distance by a predetermined first number of standard deviations.


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