Introduction to the special issue on successful real-world data mining applications

Author:

Melli Gabor1,Zaïane Osmar R.2,Kitts Brendan3

Affiliation:

1. PredictionWorks, Seattle, WA

2. University of Alberta, Edmonton, Alberta, Canada

3. Microsoft, Redmond, WA

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.

Publisher

Association for Computing Machinery (ACM)

Reference4 articles.

1. U. Fayyad G. Piatetsky-Shapiro P. Smyth R. Uthurusamy. editors. Advances in Knowledge Discovery and Data Mining. AAAI/MIT Press 1996 U. Fayyad G. Piatetsky-Shapiro P. Smyth R. Uthurusamy. editors. Advances in Knowledge Discovery and Data Mining. AAAI/MIT Press 1996

2. Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining - KDD '05

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