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Pattern Matching with Adaptive Granularity Over Streaming Time Series
A novel approach to solve fine-grained matching of streaming time series data from sensors with lower latency and limited computing resource is proposed, which outperforms the brute-force method and MSM, a multi-step filter mechanism over the multi-scaled representation, by orders of magnitude. Expand
Matching Consecutive Subpatterns Over Streaming Time Series
A novel representation Equal-Length Block (ELB) is proposed together with two efficient implementations, which work very well under all Lp-Norms without false dismissals and outperforms the brute-force method and MSM, a multi-step filter mechanism over the multi-scaled representation by orders of magnitude. Expand
Fine-Grained Pattern Matching Over Streaming Time Series
This paper introduces Equal-Length Block (ELB) representation together with Block-Skipping Pruning (BSP) policy, which guarantees low cost feature calculation, effective pruning and no false dismissals, and proposes a novel two-phase approach to fine-grained pattern matching. Expand