Invention Grant
- Patent Title: Prediction of network events via rule set representations of machine learning models
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Application No.: US17105971Application Date: 2020-11-27
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Publication No.: US11669751B2Publication Date: 2023-06-06
- Inventor: Yaron Kanza , Balachander Krishnamurthy , Sivaramakrishnan Ramanathan , Minian Yu , Jelena Mirkovic
- Applicant: AT&T Intellectual Property I, L.P. , University of Southern California , President and Fellows of Harvard College
- Applicant Address: US GA Atlanta
- Assignee: AT&T Intellectual Property I, L.P.,PRESIDENT AND FELLOWS OF HARVARD COLLEGE,UNIVERSITY OF SOUTHER CALIFORNIA
- Current Assignee: AT&T Intellectual Property I, L.P.,PRESIDENT AND FELLOWS OF HARVARD COLLEGE,UNIVERSITY OF SOUTHER CALIFORNIA
- Current Assignee Address: US GA Atlanta; US MA Cambridge; US CA Los Angeles
- Main IPC: G06F15/16
- IPC: G06F15/16 ; G06N5/025 ; H04L43/0876 ; H04L43/067 ; H04L41/16 ; H04L41/08
Abstract:
A processing system including at least one processor may obtain a time series of measurement values from a communication network and train a prediction model in accordance with the time series of measurement values to predict future instances of an event of interest, where the time series of measurement values is labeled with one or more indicators of instances of the event of interest. The processing system may then generate a deterministic finite automaton based upon the prediction model, convert the deterministic finite automaton into a rule set, and deploy the rule set to at least one network component of the communication network.
Public/Granted literature
- US20220172076A1 PREDICTION OF NETWORK EVENTS VIA RULE SET REPRESENTATIONS OF MACHINE LEARNING MODELS Public/Granted day:2022-06-02
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