Show Me Your Friends and I’ll Tell You Who You Are. Finding Anomalous Time Series by Conspicuous Cluster Transitions

Alone We Can Do So Little; Together We Cannot Be Detected

“…Moreover, the results are based on a much more intuitive threshold that incorporates the cluster membership of time series. We compare the obtained results with those of Tatusch et al [16].…”

“…Since we compared our procedure with that of Tatusch et al [16], we adapted the definitions they provided.…”

“…Although the results are convincing, the given method is not applicable to streaming data because it is decidedly computationally intensive. Furthermore, the approach of Tatusch et al [16] requires the user to set a threshold, which is based on the time-series over-time stability. However, the construct of this stability measure is not intuitive; therefore, it may be very difficult to find appropriate values for the threshold.…”

“…Then, we propose an optimization to reduce the number of computations required and, thus, to improve the performance of our method. In Section 4, we compare the results of our method with the results of Tatusch et al [16], a solution with a similar key idea. To ensure a fair comparison, we use the same data set and hyperparameters as in [16].…”

“…In Section 4, we compare the results of our method with the results of Tatusch et al [16], a solution with a similar key idea. To ensure a fair comparison, we use the same data set and hyperparameters as in [16]. Finally, we conclude and discuss possible future work in Section 5.…”