Exploratory mining and pruning optimizations of constrained associations rules
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Knowledge discovery in data warehouses
ACM SIGMOD Record
Principles of data mining
Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Discovery-Driven Exploration of OLAP Data Cubes
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Sequential PAttern mining using a bitmap representation
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Using Datacube Aggregates for Approximate Querying and Deviation Detection
IEEE Transactions on Knowledge and Data Engineering
CEC '05 Proceedings of the Seventh IEEE International Conference on E-Commerce Technology
Design and Implementation of Commerce Data Mining System Based on Rough Set Theory
ICEBE '05 Proceedings of the IEEE International Conference on e-Business Engineering
Study and Applications of Data Mining to the Structure Risk Analysis of Customs Declaration Cargo
ICEBE '05 Proceedings of the IEEE International Conference on e-Business Engineering
A knowledge mining framework for business analysts
ACM SIGMIS Database
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There is an extensive literature on data mining techniques, including several applications of these techniques in the e-commerce setting. However, all previous approaches require that expert users interpret the data mining results, making them cumbersome to use by business analysts. In this work, we describe a framework that shows how data mining technology can be effectively applied in an e-commerce environment, delivering significant benefits to the business analyst. Using a real-world case study, we demonstrate the added benefit of the proposed method. We also validate the claim that the produced results represent actionable knowledge that can help the business analyst improve the business performance, by significantly reducing the time needed for data analysis, which results in substantial financial savings.