Invention Grant
- Patent Title: Machine-learning-based techniques for predictive monitoring of a software application framework
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Application No.: US17127216Application Date: 2020-12-18
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Publication No.: US12169699B2Publication Date: 2024-12-17
- Inventor: Shashank Prasad Rao , Karthik Muralidharan
- Applicant: ATLASSIAN PTY LTD. , ATLASSIAN US, INC.
- Applicant Address: AU Sydney; US CA San Francisco
- Assignee: ATLASSIAN PTY LTD.,ATLASSIAN US, INC.
- Current Assignee: ATLASSIAN PTY LTD.,ATLASSIAN US, INC.
- Current Assignee Address: AU Sydney; US CA San Francisco
- Agency: Alston & Bird LLP
- Main IPC: G06F40/58
- IPC: G06F40/58 ; G06F11/30 ; G06F11/34 ; G06N20/00

Abstract:
Systems and methods provide techniques for more effective and efficient predictive monitoring of a software application framework. In response, embodiments of the present invention provide methods, apparatuses, systems, computing devices, and/or the like that are configured to enable effective and efficient predictive monitoring of a software application framework using incident signatures for the software application that are generated by using a natural language processing machine learning framework, a structured data processing machine learning model, a feature combination machine learning model, and a clustering machine learning model.
Public/Granted literature
- US20220198156A1 MACHINE-LEARNING-BASED TECHNIQUES FOR PREDICTIVE MONITORING OF A SOFTWARE APPLICATION FRAMEWORK Public/Granted day:2022-06-23
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