TOP-10 DATA MINING CASE STUDIES
| Autor: | Bart Goethals, Paul Beinat, Geoffrey J. McLachlan, Longbing Cao, Gabor Melli, Xindong Wu, Osmar R. Zaïane, Francesco Bonchi, Rong Duan, Christos Faloutsos, Rayid Ghani, Jian Pei, Brendan Kitts, Ashok Srivastava |
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| Rok vydání: | 2012 |
| Předmět: |
Computer. Automation
Data stream mining Computer science Economics computer.software_genre Data science Knowledge extraction Data mining cost-benefit analysis case study 68T05 68U30 68-01 Computer Science (miscellaneous) Domain knowledge Snapshot (computer storage) Artificial Intelligence & Image Processing Data mining computer Mathematics Panel discussion |
| Zdroj: | International journal of information technology & decision making |
| ISSN: | 0219-6220 |
| Popis: | 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. © 2012 World Scientific Publishing Company. |
| Databáze: | OpenAIRE |
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