Invention Grant
- Patent Title: On demand synthetic data matrix generation
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Application No.: US15803501Application Date: 2017-11-03
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Publication No.: US10791035B2Publication Date: 2020-09-29
- Inventor: Tejaswini Ganapathi , Satish Raghunath , Xu Che , Shauli Gal , Andrey Karapetov
- Applicant: salesforce.com, inc.
- Applicant Address: US CA San Francisco
- Assignee: salesforce.com, inc.
- Current Assignee: salesforce.com, inc.
- Current Assignee Address: US CA San Francisco
- Agency: Wong & Rees LLP
- Agent Kirk D. Wong
- Main IPC: H04L12/24
- IPC: H04L12/24 ; G06F17/16 ; H04L12/26 ; G06N7/00 ; G05B17/02 ; G06F16/2458
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
- US20190140910A1 ON DEMAND SYNTHETIC DATA MATRIX GENERATION Public/Granted day:2019-05-09
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