Building the data warehouse (2nd ed.)
Building the data warehouse (2nd ed.)
A database perspective on knowledge discovery
Communications of the ACM
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Towards on-line analytical mining in large databases
ACM SIGMOD Record
Knowledge discovery in data warehouses
ACM SIGMOD Record
PARSIMONY: An infrastructure for parallel multidimensional analysis and data mining
Journal of Parallel and Distributed Computing - Special issue on high-performance data mining
Multi-dimensional sequential pattern mining
Proceedings of the tenth international conference on Information and knowledge management
iDiff: Informative Summarization of Differences in Multidimensional Aggregates
Data Mining and Knowledge Discovery
Cubegrades: Generalizing Association Rules
Data Mining and Knowledge Discovery
Discovery-Driven Exploration of OLAP Data Cubes
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Mining Multi-Dimensional Constrained Gradients in Data Cubes
Proceedings of the 27th International Conference on Very Large Data Bases
A New SQL-like Operator for Mining Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Scalable Classification over SQL Databases
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Viewpoints on obtaining aggregated value sets
ICCOMP'07 Proceedings of the 11th WSEAS International Conference on Computers
Warehousing complex data from the web
International Journal of Web Engineering and Technology
Algorithms used to obtain aggregated value sets from relational databases
MCBE'08 Proceedings of the 9th WSEAS International Conference on Mathematics & Computers In Business and Economics
Database analysis models used for studying the residential assemble market
WSEAS Transactions on Information Science and Applications
What Can Formal Concept Analysis Do for Data Warehouses?
ICFCA '09 Proceedings of the 7th International Conference on Formal Concept Analysis
Study on residential assemblies: database and algorithms
MCBE'09 Proceedings of the 10th WSEAS international conference on Mathematics and computers in business and economics
RoK: Roll-Up with the K-Means Clustering Method for Recommending OLAP Queries
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
Analyses and algorithms for exploring relational databases
ICCOMP'09 Proceedings of the WSEAES 13th international conference on Computers
Augmenting OLAP exploration with dynamic advanced analytics
Proceedings of the 13th International Conference on Extending Database Technology
Finding an application-appropriate model for XML data warehouses
Information Systems
Algorithm using hypercube for aggregations
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
Dynamic method materialization: a framework for optimizing data access via methods
DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
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Nowadays, decision support systems are evolving in order to handle complex data. Some recent works have shown the interest of combining on-line analysis processing (OLAP) and data mining. We think that coupling OLAP and data mining would provide excellent solutions to treat complex data. To do that, we propose an enhanced OLAP operator based on the agglomerative hierarchical clustering (AHC). The here proposed operator, called OpAC (Operator for Aggregation by Clustering) is able to provide significant aggregates of facts refereed to complex objects. We complete this operator with a tool allowing the user to evaluate the best partition from the AHC results corresponding to the most interesting aggregates of facts.