2022
DOI: 10.1002/smr.2426
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FlexParser—The adaptive log file parser for continuous results in a changing world

Abstract: Any modern system writes events into files, called log files. Those contain crucial information which are subject to various analyses. Examples range from cybersecurity, intrusion detection over usage analyses to trouble shooting. Before data analysis is possible, desired information needs to be extracted first out of the semi-structured log messages. State-of-the-art event parsing often assumes static log events. However, any modern system is updated consistently and with updates also log file structures can … Show more

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Cited by 8 publications
(2 citation statements)
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“…It uses a transfer learning technique together with the deep neural network to balance the trade-off between the accuracy of the extracted template and human resources for manual labeling. FlexParser [25] trains a stateful LSTM to parse logs.…”
Section: Pattern Aware Log Parsingmentioning
confidence: 99%
See 1 more Smart Citation
“…It uses a transfer learning technique together with the deep neural network to balance the trade-off between the accuracy of the extracted template and human resources for manual labeling. FlexParser [25] trains a stateful LSTM to parse logs.…”
Section: Pattern Aware Log Parsingmentioning
confidence: 99%
“…A number of template mining algorithms were proposed [2,13,16,[24][25][26], which enable the automatic extraction of templates. However, previous template mining algorithms do not support interactive log analysis, which is highly desirable in real-world diagnosis or troubleshooting of Web applications.…”
Section: Introductionmentioning
confidence: 99%