Outlier Ranking via Subspace Analysis in Multiple Views of the Data

  title={Outlier Ranking via Subspace Analysis in Multiple Views of the Data},
  author={Emmanuel M{\"u}ller and Ira Assent and Patricia Iglesias S{\'a}nchez and Yvonne M{\"u}lle and Klemens B{\"o}hm},
  journal={2012 IEEE 12th International Conference on Data Mining},
Outlier mining is an important task for finding anomalous objects. In practice, however, there is not always a clear distinction between outliers and regular objects as objects have different roles w.r.t. different attribute sets. An object may deviate in one subspace, i.e. a subset of attributes. And the same object might appear perfectly regular in other subspaces. One can think of subspaces as multiple views on one database. Traditional methods consider only one view (the full attribute… CONTINUE READING

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