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LOG ANALYSIS SYSTEM EMPLOYING LONG SHORT-TERM MEMORY RECURRENT NEURAL NETWORKS
LOG ANALYSIS SYSTEM EMPLOYING LONG SHORT-TERM MEMORY RECURRENT NEURAL NETWORKS
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机译:日志分析系统采用长短期内存经常性神经网络
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摘要
System logs are processed to identify and report anomalies in execution of processes of a log-generating system such as a data storage system. Log messages of system logs are vectorized to generate log-message vectors; long short-term memory (LSTM) neural network processing is applied to the log-message vectors to generate an LSTM output sequence representing a production flow of the processes; and second-level neural network processing is applied to a combination of the LSTM output sequence and a training sequence to generate an analysis sequence containing a representation of anomalies in the production flow of the processes, where the training sequence is generated from a non-anomalous training flow. An anomaly report is generated and provided to a report consumer for taking further action with respect to the anomalies represented in the analysis sequence.
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