公开(公告)号：US09613319B1

公开(公告)日：2017-04-04

申请号：US14820416

申请日：2015-08-06

Applicant: Veritas Technologies LLC

Inventor： Shengke Yu ,  Venkat Rangan

IPC: G06F17/30 ,  G06N99/00

CPC classification number: G06N99/005 ,  G06F17/30011 ,  G06F17/30598 ,  G06F17/30707

Abstract: A server computing system determines a plurality of statistics for a plurality of test documents, determines a number of false negatives for a corpus of documents based on one or more of the plurality of statistics for the plurality of test documents. The classification of a document of the corpus of documents is a false negative if classification of the document by a classification model is negative and classification of the document by a user is positive. The server computing system calculates an effectiveness of an information retrieval system on a corpus of documents based on the number of false negatives for the corpus of documents.

公开(公告)号：US09607272B1

公开(公告)日：2017-03-28

申请号：US13843501

申请日：2013-03-15

Applicant: Veritas Technologies LLC

Inventor： Shengke Yu ,  Venkat Rangan

IPC: G06N99/00

CPC classification number: G06N99/005

Abstract: A predictive coding system updates a plurality of training documents for an untrained classification model based on a plurality of additional documents. The plurality of additional documents are selected from a plurality of unlabeled documents based on a decision hyperplane associated with a first trained classification model. The predictive coding system provides the updated plurality of training documents to the untrained classification model to cause the untrained classification model to be retrained and to cause a second trained classification model to be generated.