Outlier Detection and Trend Detection: Two Sides of the Same Coin

  title={Outlier Detection and Trend Detection: Two Sides of the Same Coin},
  author={Erich Schubert and Michael Weiler and A. Zimek},
  journal={2015 IEEE International Conference on Data Mining Workshop (ICDMW)},
Outlier detection is commonly defined as the process of finding unusual, rare observations in a large data set, without prior knowledge of which objects to look for. Trend detection is the task of finding some unexpected change in some quantity, such as the occurrence of certain topics in a textual data stream. Many established outlier detection methods are designed to search for low-density objects in a static data set of vectors in Euclidean space. For trend detection, high volume events are… Expand
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