Efficient parallel data mining for association rules
CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
A tree projection algorithm for generation of frequent item sets
Journal of Parallel and Distributed Computing - Special issue on high-performance data mining
Hash based parallel algorithms for mining association rules
DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
Parallel Mining of Association Rules
IEEE Transactions on Knowledge and Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
A high-performance distributed algorithm for mining association rules
Knowledge and Information Systems
A Fast Parallel Association Rules Mining Algorithm Based on FP-Forest
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II
Pfp: parallel fp-growth for query recommendation
Proceedings of the 2008 ACM conference on Recommender systems
Deriving strong association mining rules using a dependency criterion, the lift measure
International Journal of Data Analysis Techniques and Strategies
Performance study of distributed Apriori-like frequent itemsets mining
Knowledge and Information Systems
Using a cosine-type measure to derive strong association mining rules
International Journal of Knowledge Engineering and Data Mining
Frequent itemset mining with parallel RDBMS
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
A distributed recommender system architecture
International Journal of Web Engineering and Technology
Proceedings of the WICSA/ECSA 2012 Companion Volume
An effective rule miner for instance matching in a web of data
Proceedings of the 21st ACM international conference on Information and knowledge management
A parallel association-rule mining algorithm
WISM'12 Proceedings of the 2012 international conference on Web Information Systems and Mining
Accelerating frequent itemset mining on graphics processing units
The Journal of Supercomputing
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FP-growth has become a popular algorithm to mine frequent patterns. Its metadata FP-tree has allowed significant performance improvement over previously reported algorithms. However that special data structure also restrict the ability for further extensions. There is also potential problem when FP-tree can not fit into the memory. In this paper, we report parallel execution of FP-growth. We examine the bottlenecks of the parallelization and also method to balance the execution efficiently on shared-nothing environment.