ACM Transactions on Database Systems (TODS)
Improvements on a heuristic algorithm for multiple-query optimization
Data & Knowledge Engineering
Query flocks: a generalization of association-rule mining
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Exploratory mining and pruning optimizations of constrained associations rules
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Simultaneous optimization and evaluation of multiple dimensional queries
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Optimization of constrained frequent set queries with 2-variable constraints
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Efficient mining of emerging patterns: discovering trends and differences
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
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
Efficient and extensible algorithms for multi query optimization
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Molecular feature mining in HIV data
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
ACM SIGKDD Explorations Newsletter
Discovery in multi-attribute data with user-defined constraints
ACM SIGKDD Explorations Newsletter
Detecting Group Differences: Mining Contrast Sets
Data Mining and Knowledge Discovery
Using Common Subexpressions to Optimize Multiple Queries
Proceedings of the Fourth International Conference on Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Mining Frequent Item Sets with Convertible Constraints
Proceedings of the 17th 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
Answering queries using views: A survey
The VLDB Journal — The International Journal on Very Large Data Bases
DualMiner: a dual-pruning algorithm for itemsets with constraints
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficiently mining frequent trees in a forest
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
A Theory of Inductive Query Answering
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Multiple Query Optimization for Data Analysis Applications on Clusters of SMPs
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
An Algebra for Inductive Query Evaluation
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
On detecting differences between groups
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Multi-relational data mining: an introduction
ACM SIGKDD Explorations Newsletter
Scalability and efficiency in multi-relational data mining
ACM SIGKDD Explorations Newsletter
State of the art of graph-based data mining
ACM SIGKDD Explorations Newsletter
CrossMine: Efficient Classification Across Multiple Database Relations
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Mining Closed Relational Graphs with Connectivity Constraints
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Multiple-Objective Compression of Data Cubes in Cooperative OLAP Environments
ADBIS '08 Proceedings of the 12th East European conference on Advances in Databases and Information Systems
Journal of Intelligent Information Systems
ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
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With an increasing use of data mining tools and techniques, we envision that a Knowledge Discovery and Data Mining System (KDDMS) will have to support and optimize for the following scenarios: 1) Sequence of Queries: A user may analyze one or more datasets by issuing a sequence of related complex mining queries, and 2) Multiple Simultaneous Queries: Several users may be analyzing a set of datasets concurrently, and may issue related complex queries.This paper presents a systematic mechanism to optimize for the above cases, targetting the class of mining queries involving frequent pattern mining on one or multiple datasets. We present a system architecture and propose new algorithms for this purpose. We show the design of a knowledgeable cache which can store the past query results from queries on multiple datasets. We present algorithms which enable the use of the results stored in such a cache to further optimize multiple queries.We have implemented and evaluated our system with both real and synthetic datasets. Our experimental results show that our techniques can achieve a speedup of up to a factor of 9, compared with the systems which do not support caching or optimize for multiple queries.