The detection of recurring behavioral patterns in time series data, also called motif discovery, is a crucial step for mining insights complex especially environments where manual monitoring not feasible. However, current state-of-the-art algorithms fall short their applicability production (due to static length, lots user defined parameters, only providing the best pair, etc.). In this paper, ...