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| Titel: |
A comprehensive survey of numeric and symbolic outlier mining techniques |
| Auteur: |
Agyemang, Malik Barker, Ken Alhajj, Rada |
| Verschenen in: |
Intelligent data analysis |
| Paginering: | Jaargang 10 (2006) nr. 6 pagina's 521-538 |
| Jaar: |
2006-11-27 |
| Inhoud: |
Data that appear to have different characteristics than the rest of the population are called outliers. Identifying outliers from huge data repositories is a very complex task called outlier mining. Outlier mining has been akin to finding needles in a haystack. However, outlier mining has a number of practical applications in areas such as fraud detection, network intrusion detection, and identification of competitor and emerging business trends in e-commerce. This survey discuses practical applications of outlier mining, and provides a taxonomy for categorizing related mining techniques. A comprehensive review of these techniques with their advantages and disadvantages along with some current research issues are provided. |
| Uitgever: |
IOS Press |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 1 van 7 gevonden artikelen
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