On the use of Machine Learning and Deep Learning for Text Similarity and Categorization and its Application to Troubleshooting Automation
On the use of Machine Learning and Deep Learning for Text Similarity and Categorization and its Application to Troubleshooting Automation
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Date
2022-01-04
Authors
Couto, Julia
Tomaz, Laura
Godoy, Julia
Kniest, Davi
Callegari, Daniel
Meneguzzi, Felipe
Ruiz, Duncan
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Abstract
Troubleshooting is a labor-intensive task that includes repetitive solutions to similar problems. This task can be partially or fully automated using text-similarity matching to find previous solutions, lowering the workload of technicians. We develop a systematic literature review to identify the best approaches to solve the problem of troubleshooting automation and classify incidents effectively. We identify promising approaches and point in the direction of a comprehensive set of solutions that could be employed in solving the troubleshooting automation problem.
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Keywords
Text Analytics,
deep learning,
machine learning,
text categorization,
text similarity,
troubleshooting automation
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10 pages
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Proceedings of the 55th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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