Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Knowledge Discovery in Databases
Knowledge Discovery in Databases
The Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Are you becoming a diabetic? a data mining approach
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
A user driven data mining process model and learning system
DASFAA'08 Proceedings of the 13th international conference on Database systems for advanced applications
Towards the Generic Framework for Utility Considerations in Data Mining Research
Proceedings of the 2010 conference on Data Mining for Business Applications
Mining rare association rules in the datasets with widely varying items' frequencies
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I
An efficient approach to mine rare association rules using maximum items' support constraints
BNCOD'10 Proceedings of the 27th British national conference on Data Security and Security Data
A data analytics application assessing pavement deflection factors for a road network
Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services
A data analytics case study assessing factors affecting pavement deflection values
International Journal of Business Intelligence and Data Mining
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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.