Rule+Exception Learning-Based Class Specification and Labeling in Intelligence and Security Analysis

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Abstract

One of the key tasks in intelligence and security informatics (ISI) is to find anomalies and exceptions from typically voluminous datasets and observations [1-4]. For example, in the context of societal security, finding “exceptions” may involve discovering irregular behaviors in a community where it is assumed that most people behave normally.