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Intrusion detection systems (IDS) usually trigger a great number of alarm messages that frequently overwhelm their human operators. Hierarchically clustering technique is able to help IDS operators to get meaningful overviews from the great number of alarms. A dilemma is encountered when the clusters are generated. If the clusters are obtained one by one, they cannot be prevented from overlapping...
The k-means clustering problem is a famous problem with a variety of applications. It can be summarized as finding the best k representative centers for an input data set. K-means algorithm and its variations are known to be fast approximation iterative algorithms to the problem. However, several studies have shown that the genetic algorithm (GA) performs more favorably. In this paper, a new crossover...
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