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 data streams under block evolution
ACM SIGKDD Explorations Newsletter
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
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Intelligent Rollups in Multidimensional OLAP Data
Proceedings of the 27th International Conference on Very Large Data Bases
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Sequential PAttern mining using a bitmap representation
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Finding surprising patterns in a time series database in linear time and space
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Entropy Based Approximate Querying and Exploration of Datacubes
SSDBM '01 Proceedings of the 13th International Conference on Scientific and Statistical Database Management
On-Line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms
Data Mining and Knowledge Discovery
Privacy preserving mining of association rules
Information Systems - Knowledge discovery and data mining (KDD 2002)
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 framework for projected clustering of high dimensional data streams
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Efficiently Discovering Recent Frequent Items in Data Streams
SSDBM '08 Proceedings of the 20th international conference on Scientific and Statistical Database Management
Knowledge Mining for the Business Analyst
DEXA '08 Proceedings of the 19th international conference on Database and Expert Systems Applications
Frequent items in streaming data: An experimental evaluation of the state-of-the-art
Data & Knowledge Engineering
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Several studies have focused on problems related to data mining techniques, including several applications of these techniques in the e-commerce setting. In this work, we describe how data mining technology can be effectively applied in an e-commerce environment, delivering significant benefits to the business analyst. We propose a framework that takes the results of the data mining process as input, and converts these results into actionable knowledge, by enriching them with information that can be readily interpreted by the business analyst. The framework can accommodate various data mining algorithms, and provides a customizable user interface. We experimentally evaluate the proposed approach by using a real-world case study that demonstrates the added benefit of the proposed method. The same study validates the claim that the produced results represent actionable knowledge that can help the business analyst improve the business performance, since it significantly reduces the time needed for data analysis, which results in substantial financial savings.