Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Database Mining: A Performance Perspective
IEEE Transactions on Knowledge and Data Engineering
A Parallel Apriori Algorithm for Frequent Itemsets Mining
SERA '06 Proceedings of the Fourth International Conference on Software Engineering Research, Management and Applications
Top 10 algorithms in data mining
Knowledge and Information Systems
Mining Weighted Association Rules without Preassigned Weights
IEEE Transactions on Knowledge and Data Engineering
An Efficient Association Rule Mining Algorithm In Distributed Databases
WKDD '08 Proceedings of the First International Workshop on Knowledge Discovery and Data Mining
Hardware-Enhanced Association Rule Mining with Hashing and Pipelining
IEEE Transactions on Knowledge and Data Engineering
Frequent itemset mining on graphics processors
Proceedings of the Fifth International Workshop on Data Management on New Hardware
Parallel and Distributed Frequent Pattern Mining in Large Databases
HPCC '09 Proceedings of the 2009 11th IEEE International Conference on High Performance Computing and Communications
Scalable APRIORI-Based Frequent Pattern Discovery
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 01
A load-balanced distributed parallel mining algorithm
Expert Systems with Applications: An International Journal
Parallel TID-based frequent pattern mining algorithm on a PC Cluster and grid computing system
Expert Systems with Applications: An International Journal
A Dynamic Approach for Frequent Pattern Mining Using Transposition of Database
ICCSN '10 Proceedings of the 2010 Second International Conference on Communication Software and Networks
Knowledge-Based Interactive Postmining of Association Rules Using Ontologies
IEEE Transactions on Knowledge and Data Engineering
A New Method for Eliminating Redundant Association Rules
ICICTA '10 Proceedings of the 2010 International Conference on Intelligent Computation Technology and Automation - Volume 01
Advanced Version of A Priori Algorithm
ICIIC '10 Proceedings of the 2010 First International Conference on Integrated Intelligent Computing
Data Mining: Practical Machine Learning Tools and Techniques
Data Mining: Practical Machine Learning Tools and Techniques
Design and Analysis of a Reconfigurable Platform for Frequent Pattern Mining
IEEE Transactions on Parallel and Distributed Systems
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We propose a scheduling strategy in this paper to address the load imbalance problem of the distributed parallel apriori (DPA) algorithm published recently. We use fine grained tasks that are derived by dividing the tasks defined by DPA into smaller subtasks. The subtasks will be scheduled by a dynamic self-scheduling scheme for better load balance. Furthermore, we propose two different methods for data transmission from the master to workers. The first one broadcasts all the frequent k-itemsets to all work nodes while the second one transmits only the required data to each individual work node. Experimental results demonstrate the proposed two approaches both outperform DPA. The first one is more suitable for small datasets and the second one provides steadier performance improvement no matter which self-scheduling scheme is adopted.