Time series anomaly discovery with grammar-based compression

@inproceedings{Senin2015TimeSA,
  title={Time series anomaly discovery with grammar-based compression},
  author={Pavel Senin and Jessica D Lin and Xing Wang and Tim Oates and Sunil Gandhi and Arnold P. Boedihardjo and Crystal Chen and Susan Frankenstein},
  booktitle={EDBT},
  year={2015}
}
The problem of anomaly detection in time series has recently received much attention. However, many existing techniques require the user to provide the length of a potential anomaly, which is often unreasonable for real-world problems. In addition, they are also often built upon computing costly distance functions – a procedure that may account for up to 99% of an algorithm’s computation time. Addressing these limitations, we propose two algorithms that use grammar induction to aid anomaly… CONTINUE READING

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