VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
On the Computation of Multidimensional Aggregates
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
A Distributed OLAP Infrastructure for E-Commerce
COOPIS '99 Proceedings of the Fourth IECIS International Conference on Cooperative Information Systems
Relative Prefix Sums: An Efficient Approach for Querying Dynamic OLAP Data Cubes
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Enhancing Preprocessing in Data-Intensive Domains using Online-Analytical Processing
DaWaK 2000 Proceedings of the Second International Conference on Data Warehousing and Knowledge Discovery
User Defined Partitioning - Group Data Based on Computation Model
DaWaK '08 Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery
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Profiling customers' behavior has become increasingly important for many applications such as fraud detection, targeted marketing and promotion. Customer behavior profiles are created from very large collections of transaction data. This has motivated us to develop a data-warehouse and OLAP based, scalable and flexible profiling engine. We define profiles by probability distributions, and compute them using OLAP operations on multidimensional and multilevel data cubes. Our experience has revealed the simplicity and power of OLAP-based solutions to scalable profiling and pattern analysis.