Slide 19
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19 BUILD SOFTWARE TO TEST SOFTWARE
QA Meetup
Unsupervised learning for anomaly detection
● A detection model is constructed using historical logs, which
describe a variety of events of software systems.
The model is used for:
○ detecting various types of system behavior anomalies
○ determining statistical load parameters
● Another way is to extract semantic information of log events.
The anomalies are detected from the contextual information in the
log sequences based on the importance of different log events.
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