Patent · US Active

Data quality assessment for vector machine learning

US9015082B1 · kind B1 · utility

13Cited by

6References

18Claims

0Family size

Assignee

Symantec Corporation · US

Inventors

Sumesh Jaiswal · Pune, IN
Ashish D. Aggarwal · Los Altos Hills, US
Phillip DiCorpo · San Francisco, US
Shitalkumar S. Sawant · Fremont, US
Sally Kauffman · Washington, US
Alan Dale Galindez · Menlo Park, US

Key dates

Filing date	Dec 14, 2011
Grant date	Apr 21, 2015
Priority date	—
Expiry date	Aug 19, 2033

Classification

Technology area (CPC H)Electricity
CPC primaryH04L63/20
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

A computing device receives a training data set that comprises a plurality of sensitive documents and a plurality of non-sensitive documents. The computing device determines a quality of the training data set. The quality may be determined using k-fold cross validation and/or latent semantic indexing. In response to determining that the training data set has a satisfactory quality, the computing device then analyzes the training data set using machine learning to train a machine learning-based detection (MLD) profile, the MLD profile to be used by a data loss prevention (DLP) system to classify new documents as sensitive documents or as non-sensitive documents.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.