Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
A database perspective on knowledge discovery
Communications of the ACM
Using a knowledge cache for interactive discovery of association rules
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Sampling Large Databases for Association Rules
VLDB '96 Proceedings of the 22th 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
Itemset Materializing for Fast Mining of Association Rules
ADBIS '98 Proceedings of the Second East European Symposium on Advances in Databases and Information Systems
SQL-like language for database mining
ADBIS'97 Proceedings of the First East-European conference on Advances in Databases and Information systems
Composition of Mining Contexts for Efficient Extraction of Association Rules
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
Using Condensed Representations for Interactive Association Rule Mining
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Data Access Paths for Frequent Itemsets Discovery
ADBIS '02 Proceedings of the 6th East European Conference on Advances in Databases and Information Systems
Incremental association rule mining using materialized data mining views
ADVIS'04 Proceedings of the Third international conference on Advances in Information Systems
Incremental data mining using concurrent online refresh of materialized data mining views
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
Optimizing a sequence of frequent pattern queries
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
On multiple query optimization in data mining
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Computation of mining queries: an algebraic approach
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
Partition-Based approach to processing batches of frequent itemset queries
FQAS'06 Proceedings of the 7th international conference on Flexible Query Answering Systems
A Framework for Synthesizing Arbitrary Boolean Queries Induced by Frequent Itemsets
International Journal of Knowledge-Based Organizations
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Data mining is a useful decision support technique, which can be used to find trends and regularities in warehouses of corporate data. A serious problem of its practical applications is long processing time required by data mining algorithms. Current systems consume minutes or hours to answer simple queries. In this paper we present the concept of materialized data mining views. Materialized data mining views store selected patterns discovered in a portion of a database, and are used for query rewriting, which transforms a data mining query into a query accessing a materialized view. Since the transformation is transparent to a user, materialized data mining views can be created and used like indexes.