2006 IntroToSpecialIssueSRWDMApps
- (Melli et al., 2006b) ⇒ Gabor Melli, Osmar R. Zaïane, and Brendan Kitts. (2006). “Introduction to the Special Issue on Successful Real-World Data Mining Applications.” In: ACM SIGKDD Explorations Newsletter, 8(1). doi:10.1145/1147234.1147235
Subject Headings: Data Mining Case Study.
Notes
- Alternate URL: http://www.sigkdd.org/explorations/issue8-1/0-Melli.pdf
Cited By
- ~18 http://scholar.google.ca/scholar?hl=en&q=%22Introduction+to+the+Special+Issue+on+Successful+Real-World+Data+Mining+Applications%22+2006
- ~3 https://dl.acm.org/citation.cfm?id=1147234.1147235&preflayout=flat
2009
- (Kiran & Re, 2009) ⇒ R. Uday kiran, and P. Krishna Re. (2009). “An Improved Multiple Minimum Support Based Approach to Mine Rare Association Rules. In: IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2009). doi:10.1109/CIDM.2009.4938669
2008
- (Ge et al., 2008) ⇒ Esther Ge, Richi Nayak, Yue Xu, Yuefeng Li. (2008). “A user driven data mining process model and learning system.” In: Proceedings of the 13th International Conference on Database systems for advanced applications.
Quotes
Abstract
Since its inception, the field of Data Mining and Knowledge Discovery from Databases has been driven by the need to solve practical problems [4]. From scaling to large databases and handling noisy and high-dimensional data to finding associational patterns in grocery store transaction data, data mining is a research area rich in application [1]. Despite its practical roots few case studies of data mining applications have been published. The industrial track of the annual SIGKDD conference has provided one such forum, but rarely do these papers present complete descriptions of deployed systems [2]. This special issue attempts to address the gap by showcasing the choices, strategies, and lessons learned from building a real-world data mining application. In a sense this collection is a follow-up to the first workshop on data mining case studies held during ICDM-2006 [3]. This issue however introduces several new papers. Of the 29 papers reviewed 10 papers were accepted. The papers come from a broad range of application areas including Customer Relationship Management, Medicine, Taxation, and Software Development.
References
- 1. Usama M. Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth, Ramasamy Uthurusamy, Advances in knowledge discovery and data mining, American Association for Artificial Intelligence, Menlo Park, CA, 1996
- 2. Robert L. Grossman, R. Bayardo, K. Bennet, and J. Vaidya, editors, Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2005), ACM Press, New York, 2005, ISBN 1-59593-135-X.
- 3. Brendan Kitts, Gabor Melli and K. Rexer, editors, Proceedings of the First Workshop on Data Mining Case Studies collocated with International Conference on Data Mining (ICDM), 2005.
- 4. Gregory Piateski, William Frawley, Knowledge Discovery in Databases, MIT Press, Cambridge, MA, 1991,
Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
---|---|---|---|---|---|---|---|---|---|---|
2006 IntroToSpecialIssueSRWDMApps | Gabor Melli Osmar R. Zaïane Brendan Kitts | Introduction to the Special Issue on Successful Real-World Data Mining Applications | ACM SIGKDD Explorations Newsletter | http://dl.acm.org/authorize?814720 | 10.1145/1147234.1147235 | 2006 |