Recent advances in data mining of enterprise data : algorithms and applications /
The main goal of the new field of data mining is the analysis of large and complex datasets. Some very important datasets may be derived from business and industrial activities. This kind of data is known as "enterprise data". The common characteristic of such datasets is that the analyst...
| Автор-организации: | International Workshop on Mining of Enterprise Data Como, Italy) |
|---|---|
| Други автори: | Liao, T. Warren 1957-, Triantaphyllou, Evangelos. |
| Формат: | Електронна книга |
| Език: | English |
| Публикувано: |
Singapore ; Hackensack, NJ :
World Scientific,
℗♭2007.
|
| Серия: |
Series on computers and operations research ;
v. 6. |
| Предмети: | |
| Онлайн достъп: |
http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=236063 |
| Подобни документи: |
Print version::
Recent advances in data mining of enterprise data. |
Съдържание:
- Ch. 1. Enterprise data mining: a review and research directions / T.W. Liao
- ch. 2. Application and comparison of classification techniques in controlling credit risk / L. Yu [and others]
- ch. 3. Predictive classification with imbalanced enterprise data / S. Daskalaki, I. Kopanas, and N.M. Avouris
- ch. 4. Using soft computing methods for time series forecasting / P.-C. Chang and Y.-W. Wang
- ch. 5. Data mining applications of process platform formation for high variety production / J. Jiao and L. Zhang
- ch. 6. A data mining approach to production control in dynamic manufacturing systems / H.-S. Min and Y. Yih
- ch. 7. Predicting wine quality from agricultural data with single-objective and multi-objective data mining algorithms / M. Last [and others]
- ch. 8. Enhancing competitive advantages and operational excellence for high-tech industry through data mining and digital management / C.-F. Chien, S.-C. Hsu, and Chia-Yu Hsu
- ch. 9. Multivariate control charts from a data mining perspective / G.C. Porzio and G. Ragozini
- ch. 10. Data mining of multi-dimensional functional data for manufacturing fault diagnosis / M.K. Jeong, S.G. Kong, and O.A. Omitaomu
- ch. 11. Maintenance planning using enterprise data mining / L.P. Khoo, Z.W. Zhong, and H.Y. Lim
- ch. 12. Data mining techniques for improving workflow model / D. Gunopulos and S. Subramaniam
- ch. 13. Mining images of cell-based assays / P. Perner
- ch. 14. Support vector machines and applications / T.B. Trafalis and O.O. Oladunni
- ch. 15. A survey of manifold-based learning methods / X. Huo, X. Ni, and A.K. Smith
- ch. 16. Predictive regression modeling for small enterprise data sets with bootstrap, clustering, and bagging / C.J. Feng and K. Erla.