Robust Contextual Outlier Detection: Where Context Meets Sparsity

@inproceedings{Liang2016RobustCO,
  title={Robust Contextual Outlier Detection: Where Context Meets Sparsity},
  author={Jiongqian Liang and Srinivasan Parthasarathy},
  booktitle={CIKM},
  year={2016}
}
Outlier detection is a fundamental data science task with applications ranging from data cleaning to network security. Recently, a new class of outlier detection algorithms has emerged, called contextual outlier detection, and has shown improved performance when studying anomalous behavior in a specific context. However, as we point out in this article, such approaches have limited applicability in situations where the context is sparse (i.e., lacking a suitable frame of reference). Moreover… CONTINUE READING
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