Applications of Outlier Analysis

  • Charu C. Aggarwal


Outlier analysis has numerous applications in a wide variety of domains, such as the financial industry, quality control, fault diagnosis, intrusion detection, Web analytics, and medical diagnosis. The applications of outlier analysis are so diverse that it is impossible to exhaustively cover all possibilities in a single chapter. Therefore, the goal of this chapter is to cover many problem domains at a higher level and show how they map to the various techniques discussed in earlier chapters. The practical issues and challenges in the context of real data sets will also be discussed. This will provide a broader understanding of the issues involved in problem domain to technique mapping.


Intrusion Detection Outlier Detection Anomaly Detection Unsupervised Method Supervise Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Charu C. Aggarwal
    • 1
  1. 1.IBM T.J. Watson Research CenterNew YorkUSA

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