Data stream outlier detection approach based on frequent pattern mining technique
Aiman Moyaid Said and P.D.D. Dominic (Department of Computer and Information Science, Universiti Teknologi PETRONAS, Tronoh, Perak, Malaysia), Ibrahima Faye (Department of Fundamental and Applied Science, Universiti Teknologi PETRONAS, Tronoh, Perak, Malaysia)
| Year of publication: |
2015
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|---|---|
| Authors: | Said, Aiman Moyaid ; Dominic, P. D. D. ; Faye, Ibrahima |
| Published in: |
International journal of business information systems : IJBIS. - Olney, Bucks. : Inderscience Enterprises, ISSN 1746-0972, ZDB-ID 2193362-5. - Vol. 20.2015, 1, p. 55-70
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| Subject: | data mining | data stream | outlier detection | frequent patterns mining | concept drift | static outlier detection | dynamic outlier detection | FPstream | true positive rate | TPR | false positive rate | FPR | Data Mining | Data mining | Theorie | Theory | Zeitreihenanalyse | Time series analysis | Bergbau | Mining |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10011440978