Invention Grant
- Patent Title: On demand synthetic data matrix generation
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Application No.: US17037501Application Date: 2020-09-29
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Publication No.: US12009989B2Publication Date: 2024-06-11
- Inventor: Tejaswini Ganapathi , Satish Raghunath , Xu Che , Shauli Gal , Andrey Karapetov
- Applicant: salesforce.com, inc.
- Applicant Address: US CA San Francisco
- Assignee: Salesforce, Inc.
- Current Assignee: Salesforce, Inc.
- Current Assignee Address: US CA San Francisco
- Main IPC: H04L41/14
- IPC: H04L41/14 ; G05B17/02 ; G06F16/2458 ; G06F17/16 ; G06N7/01 ; H04L41/142 ; H04L43/08 ; H04L43/0829 ; H04L43/0852 ; H04L43/087 ; H04L43/0888
Abstract:
An data driven approach to generating synthetic data matrices is presented. By retrieving historical network traffic data, probabilistic models are generated. Optimal distribution families for a set of independent data segments are determined. Applications are tested and performance metrics are determined based on the generated synthetic data matrices.
Public/Granted literature
- US20210014126A1 ON DEMAND SYNTHETIC DATA MATRIX GENERATION Public/Granted day:2021-01-14
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