On benchmarking frequent itemset mining algorithms: From measurement to analysis

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2005, Pages 36-45

  Rácz, Balázs ^a   Bodon, Ferenc ^b   Schmidt Thieme, Lars ^c  

^a INSTITUTE OF EXPERIMENTAL MEDICINE   (Hungary)

^b BUDAPEST UNIVERSITY OF TECHNOLOGY AND ECONOMICS   (Hungary)

^c UNIVERSITY OF FREIBURG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CURRENT PRACTICES; FREQUENT ITEMSET MINING;

DATA MINING;

EID: 77953573490     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1133905.1133911     Document Type: Conference Paper

References (11)

1. AMD CodeAnalyst™ Performance Analyzer. http://www.amd.com/us-en/ Processors/DevelopWithAMD/0,,30-2252-3604,00.html.
2. Intel VTune Performance Analyzers. http://www.intel.com/software/ products/vtune/.
3. Bart Goethals. Survey on frequent pattern mining. Technical report, Helsinki Institute for Information Technology, 2003.
4. Bart Goethals and Mohammed J. Zaki. Advances in frequent itemset mining implementations: Introduction to fimi03. In Bart Goethals and Mohammed J. Zaki, editors, Proceedings of the IEEE ICDM Workshop on Frequent Itemset Mining Implementations (FIMI'03), volume 90 of CEUR Workshop Proceedings, Melbourne, Florida, USA, 19. November 2003.
5. Gosta Grahne and Jianfei Zhu. Efficiently using prefix-trees in mining frequent itemsets. In Bart Goethals and Mohammed J. Zaki, editors, Proceedings of the IEEE ICDM Workshop on Frequent Itemset Mining Implementations (FIMI'03), volume 90 of CEUR Workshop Proceedings, Melbourne, Florida, USA, 19. November 2003.
6. Jiawei Han, Jian Pei, and Yiwen Yin. Mining frequent patterns without candidate generation. In Proceedings of the 2000 ACM SIGMOD international conference on Management of data, pages 1-12. ACM Press,2000.
7. Donald E. Knuth. The Art of Computer Programming. Addison-Wesley, 1968.
8. Balázs Rácz. nonordfp: An FP-growth variation without rebuilding the FP-tree. In Bart Goethals, Mohammed J. Zaki, and Roberto Bayardo, editors, Proceedings of the IEEE ICDM Workshop on Frequent Itemset Mining Implementations (FIMI'04), volume 126 of CEUR Workshop Proceedings, Brighton, UK, 1. November 2004.
9. Takeaki Uno, Masashi Kiyomi, and Hiroki Arimura. Lcm ver. 2: Efficient mining algorithms for frequent/closed/maximal itemsets. In Bart Goethals, Mohammed J. Zaki, and Roberto Bayardo, editors, Proceedings of the IEEE ICDM Workshop on Frequent Itemset Mining Implementations (FIMI'04), volume 126 of CEUR Workshop Proceedings, Brighton, UK, 1. November 2004.
10. Ke Wang, Liu Tang, Jiawei Han, and Junqiang Liu. Top down fp-growth for association rule mining. In PAKDD '02: Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, pages 334-340, London, UK, 2002. Springer-Verlag.
11. Mohammed Javeed Zaki, Srinivasan Parthasarathy, Mitsunori Ogihara, and Wei Li. New algorithms for fast discovery of association rules. In David Heckerman, Heikki Mannila, Daryl Pregibon, Ramasamy Uthurusamy, and Menlo Park, editors, Proceedings of the 3rd International Conference on Knowledge Discovery and Data Mining, pages 283-296. AAAI Press, 12-15 1997.