C4.5: programs for machine learning
C4.5: programs for machine learning
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
An effective hash-based algorithm for mining association rules
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
OLAP, relational, and multidimensional database systems
ACM SIGMOD Record
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Range queries in OLAP data cubes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
An array-based algorithm for simultaneous multidimensional aggregates
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
A statistical perspective on knowledge discovery in databases
Advances in knowledge discovery and data mining
Bayesian classification (AutoClass): theory and results
Advances in knowledge discovery and data mining
Attribute-oriented induction in data mining
Advances in knowledge discovery and data mining
Approximate computation of multidimensional aggregates of sparse data using wavelets
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Data mining: concepts and techniques
Data mining: concepts and techniques
Rough Sets, Fuzzy Sets and Knowledge Discovery
Rough Sets, Fuzzy Sets and Knowledge Discovery
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Data Mining and Knowledge Discovery
Data-Driven Discovery of Quantitative Rules in Relational Databases
IEEE Transactions on Knowledge and Data Engineering
Computing Iceberg Queries Efficiently
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Efficient and Effective Clustering Methods for Spatial Data Mining
VLDB '94 Proceedings of the 20th 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
Discovery of Multiple-Level Association Rules from Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
An Efficient Algorithm for Mining Association Rules in Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Mining Generalized Association Rules
VLDB '95 Proceedings of the 21th 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
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
SISYPHUS: the implementation of a chunk-based storage manager for OLAP data cubes
Data & Knowledge Engineering - Special issue: Advances in OLAP
A survey of data mining and knowledge discovery software tools
ACM SIGKDD Explorations Newsletter
Overcoming Limitations of Approximate Query Answering in OLAP
IDEAS '05 Proceedings of the 9th International Database Engineering & Application Symposium
Improving range-sum query evaluation on data cubes via polynomial approximation
Data & Knowledge Engineering
Answering top-k queries with multi-dimensional selections: the ranking cube approach
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Approximate range---sum query answering on data cubes with probabilistic guarantees
Journal of Intelligent Information Systems
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The problem of supporting advanced decision-support processes arise in many fields of real-life applications ranging from scenarios populated by distributed and heterogeneous data sources, such as conventional distributed data warehousing environments, to cooperative information systems. Here, data repositories expose very different formats, and knowledge representation schemes are very heterogeneous accordingly. As a consequence, a relevant research challenge is how to efficiently integrate, process and mine such distributed knowledge in order to make available it to end-users/applications in an integrated and summarized manner. Starting from these considerations, in this paper we propose an OLAM-based framework for complex knowledge pattern discovery, along with a formal model underlying this framework, called Multi-Resolution Ensemble-based Model for Advanced Knowledge Discovery in Large Databases and Data Warehouses (MRE-KDD+), and a reference architecture for such a framework. Another contribute of our work is represented by the proposal of KBMiner, a visual tool that supports the editing of evencomplex KDD processes according to the guidelines drawn by MRE-KDD+.