GPApriori: GPU-accelerated frequent itemset mining

Proceedings - IEEE International Conference on Cluster Computing, ICCC

Volumn , Issue , 2011, Pages 590-594

  Zhang, Fan ^a   Zhang, Yan ^a   Bakos, Jason ^a  

^a The Department of Mechanical Engineering   (United States)

Author keywords

Association rule mining; CUDA GPU computing; Frequent itemset mining; Parallel Computing

Indexed keywords

APRIORI; APRIORI ALGORITHMS; ASSOCIATION RULE MINING; CUDA GPU COMPUTING; DATA LAYOUTS; DATA MINING ALGORITHM; EXECUTION MODEL; FREQUENT ITEMSET MINING; FREQUENT ITEMSETS; GRAPHIC PROCESSORS; MEMORY STRUCTURE; PARALLELIZED VERSION; STATE OF THE ART;

ALGORITHMS; ARTS COMPUTING; CLUSTER COMPUTING; DATA STRUCTURES; PARALLEL ARCHITECTURES; PROGRAM PROCESSORS;

DATA MINING;

EID: 80955140474     PISSN: 15525244     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CLUSTER.2011.61     Document Type: Conference Paper

References (10)

1. R. Agrawal and H. Mannila, Fast Discovery of Association Rules, in Advances in Knowledge Discovery and Data Mining. 1996. p. 307-328.
2. R. Agrawal and R. Srikant. Fast algorithm for mining association rules. in VLDB 1994. p. 487-499
3. M. J. Zaki and K. Gouda. Fast Vertical Mining Using Diffsets. in Proc. SIGKDD. 2003. p. 326-335
4. J. Han, H. Pei, and Y. Yin. Mining Frequent Patterns without Candidate Generation. in SIGMOD. 2000. p. 1-12
5. N. Govindaraju and M. Zaki, Advances in Frequent Itemset Mining Implementations, in FIMI. 2003.
6. F. Bodon, A Trie-based APRIORI Implementation for Mining Frequent Item Sequences, in OSDM. 2005. p. 56-65.
7. C. Borgelt. Efficient Implementations of Apriori and Eclat. in Proc. FIMI. 2003.
8. M. Zaki and S. Parthasarathy, New Algorithms for Fast Discovery of Association Rules, in KDD. 1997. p. 283-296.
9. NVidia. Data Parallel Algorithm in CUDA SDK Available from: http://developer.download.nvidia.com.
10. Frequent Itemset Mining Dataset Repository Available from: http://fimi.ua.ac.be/data.