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TOP-10 DATA MINING CASE STUDIES.

Authors :
MELLI, GABOR
WU, XINDONG
BEINAT, PAUL
BONCHI, FRANCESCO
CAO, LONGBING
DUAN, RONG
FALOUTSOS, CHRISTOS
GHANI, RAYID
KITTS, BRENDAN
GOETHALS, BART
MCLACHLAN, GEOFF
PEI, JIAN
SRIVASTAVA, ASHOK
ZAÏANE, OSMAR
Source :
International Journal of Information Technology & Decision Making; Mar2012, Vol. 11 Issue 2, p389-400, 12p
Publication Year :
2012

Abstract

We report on the panel discussion held at the ICDM'10 conference on the top 10 data mining case studies in order to provide a snapshot of where and how data mining techniques have made significant real-world impact. The tasks covered by 10 case studies range from the detection of anomalies such as cancer, fraud, and system failures to the optimization of organizational operations, and include the automated extraction of information from unstructured sources. From the 10 cases we find that supervised methods prevail while unsupervised techniques play a supporting role. Further, significant domain knowledge is generally required to achieve a completed solution. Finally, we find that successful applications are more commonly associated with continual improvement rather than by single "aha moments" of knowledge ("nugget") discovery. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02196220
Volume :
11
Issue :
2
Database :
Complementary Index
Journal :
International Journal of Information Technology & Decision Making
Publication Type :
Academic Journal
Accession number :
75255349
Full Text :
https://doi.org/10.1142/S021962201240007X