Outlier mining in large high-dimensional data sets
By Fabrizio Angiulli, Clara Pizzuti. IEEE Transactions on Knowledge and Data Engineering, 2005
371 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Biomedical Engineering, Civil and Structural Engineering
View Paper: https://www.semanticscholar.org/paper/1edca00f5b118dc45dcf08ce0c4ba09f46e227c8
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Arthur Zimek
- Erich Schubert
- Hans-Peter Kriegel
- Charu C. Aggarwal
- Jörg Sander
- Fabrizio Angiulli
- Clara Pizzuti
- Stefano Basta
In Biomedical Engineering
- Arthur Zimek
- Erich Schubert
- Hans-Peter Kriegel
- Charu C. Aggarwal
- Rfdo 2XWOLHUV
- Markus Goldstein
- Ricardo José Gabrielli Barreto Campello
- Jörg Sander
In Civil and Structural Engineering
- Arthur Zimek
- Hans-Peter Kriegel
- Erich Schubert
- Charu C. Aggarwal
- Rfdo 2XWOLHUV
- Markus Goldstein
- Seiichi Uchida
- Bryan Hooi
Citations in the corpus
- A survey on unsupervised outlier detection in high‐dimensional numerical data (2012, methodology): “This idea is also used in [72,103] as a filter step before the exact computation of the top-n outliers.”
- Distance-based detection and prediction of outliers (2006, background): “guish an object as outlier on the base of the distance to its nearest neighbors [5], [6], [7], [4], [8].”