Invention Grant
- Patent Title: Correlation and root cause analysis of trace data using an unsupervised autoencoder
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Application No.: US16819881Application Date: 2020-03-16
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Publication No.: US11892938B2Publication Date: 2024-02-06
- Inventor: Matthew Green , Narayana Aditya Madineni , Michael W. Gray , Leigh S. McLean
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agent Jordan T. Schiller
- Main IPC: G06F11/00
- IPC: G06F11/00 ; G06F11/36 ; G06N3/088 ; G06N3/045

Abstract:
An analyzer system inputs parameter values from trace files of a software application into an autoencoder. The analyzer system adjusts weights of the edges between nodes in the autoencoder until reconstruction errors in outputs are minimized. The analyzer system receives a selection of a parameter represented in an autoencoder. In response, the analyzer system identifies hidden layer nodes connected to an output node corresponding to the selected parameter and identifies other output nodes connected to the hidden layer nodes. The analyzer system retrieves weights assigned to edges between the hidden layer nodes and the other output nodes. The analyzer system calculates correlation values between the output node corresponding to the selected parameter and each of the other output nodes and outputs the correlation values. A user can use the correlation values to better direct the root cause analysis.
Public/Granted literature
- US20210286707A1 CORRELATION AND ROOT CAUSE ANALYSIS OF TRACE DATA USING AN UNSUPERVISED AUTOENCODER Public/Granted day:2021-09-16
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