Comparative evaluation of anomaly detection techniques for sequence data

Varun Chandola, Varun Mithal, Vipin Kumar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

118 Scopus citations

Abstract

We present a comparative evaluation of a large number of anomaly detection techniques on a variety of publicly available as well as artificially generated data sets. Many of these are existing techniques while some are slight variants and/or adaptations of traditional anomaly detection techniques to sequence data.

Original languageEnglish (US)
Title of host publicationProceedings - 8th IEEE International Conference on Data Mining, ICDM 2008
Pages743-748
Number of pages6
DOIs
StatePublished - 2008
Event8th IEEE International Conference on Data Mining, ICDM 2008 - Pisa, Italy
Duration: Dec 15 2008Dec 19 2008

Publication series

NameProceedings - IEEE International Conference on Data Mining, ICDM
ISSN (Print)1550-4786

Other

Other8th IEEE International Conference on Data Mining, ICDM 2008
Country/TerritoryItaly
CityPisa
Period12/15/0812/19/08

Fingerprint

Dive into the research topics of 'Comparative evaluation of anomaly detection techniques for sequence data'. Together they form a unique fingerprint.

Cite this