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We present a set of novel algorithms which we call sequenceMiner that detect and characterize anomalies in large sets of high-dimensional symbol sequences that arise from recordings of switch sensors in the cockpits of commercial airliners. While the algorithms that we present are general and domain-independent, we focus on a specific problem that is critical to determining the system-wide health...
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