The technique of Knowledge Discovery in Databases(KDD) to learn valuable knowledge hidden in network alarm databases is introduced. To get such knowledge, we propose an efficient method based on sliding windows (named as Slidwin) to discover different episode rules from time sequential alarm data. The experimental results show that given different thresholds parameters, large amount of different rules could be discovered quickly.
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