Rule-based Correlation

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Rule-based Correlation is a common and traditional approach to filtering, aggregating, and correlating events that involves defining how events should be analyzed and building a rule for each combination of events. As IT infrastructures have evolved and the amount of data collected has exploded, the effort required to build rules and maintain the rules base makes this approach very cumbersome and increasingly difficult. Modern approaches using machine learning have largely made rule-based correlation obsolete.

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