H. Chen, R. H. Chiang, and V. C. Storey, Business intelligence and analytics: From big data to big impact, pp.1165-1188, 2012.

R. Anand, Mining of massive datasets

B. Goethals, Memory issues in frequent itemset mining, Proceedings of the 2004 ACM symposium on Applied computing , SAC '04, pp.530-534, 2004.
DOI : 10.1145/967900.968012

T. White, Hadoop : the definitive guide

C. Bizer, P. A. Boncz, M. L. Brodie, and O. Erling, The meaningful use of big data, ACM SIGMOD Record, vol.40, issue.4, pp.56-60, 2011.
DOI : 10.1145/2094114.2094129

J. Dean and S. Ghemawat, MapReduce, Communications of the ACM, vol.51, issue.1, pp.107-113, 2008.
DOI : 10.1145/1327452.1327492

R. Agrawal and R. Srikant, Fast algorithms for mining association rules in large databases, Proceedings of International Conference on Very Large Data Bases (VLDB), pp.487-499, 1994.

A. Savasere, E. Omiecinski, and S. B. Navathe, An efficient algorithm for mining association rules in large databases, Proceedings of International Conference on Very Large Data Bases (VLDB), pp.432-444, 1995.

Y. Tsay and Y. Chang-chien, An efficient cluster and decomposition algorithm for mining association rules, Information Sciences, vol.160, issue.1-4, pp.161-171, 2004.
DOI : 10.1016/j.ins.2003.08.013

S. Even, Graph algorithms, 1979.
DOI : 10.1017/CBO9781139015165

H. Li, Y. Wang, D. Zhang, M. Zhang, and E. Y. Chang, Pfp, Proceedings of the 2008 ACM conference on Recommender systems, RecSys '08, pp.107-114, 2008.
DOI : 10.1145/1454008.1454027

S. Owen, Mahout in action, p.2012

W. Song, B. Yang, and Z. Xu, Index-bittablefi: An improved algorithm for mining frequent itemsets. Knowl.-Based Syst, pp.507-513, 2008.

N. Jayalakshmi, V. Vidhya, M. Krishnamurthy, and A. Kannan, Frequent Itemset Generation using Double Hashing Technique, Procedia Engineering, vol.38, issue.0, pp.1467-1478, 2012.
DOI : 10.1016/j.proeng.2012.06.181

P. Han and Y. , Mining frequent patterns without candidate generation, SIGMODREC: ACM SIGMOD Record, vol.29, 2000.

M. Riondato, J. A. Debrabant, R. Fonseca, and E. Upfal, PARMA, Proceedings of the 21st ACM international conference on Information and knowledge management, CIKM '12, pp.85-94, 2012.
DOI : 10.1145/2396761.2396776

M. Liroz-gistau, R. Akbarinia, E. Pacitti, F. Porto, and P. Valduriez, Dynamic Workload-Based Partitioning Algorithms for Continuously Growing Databases. Transactions on Large-Scale Data-and Knowledge-Centered Systems, p.105, 2014.
URL : https://hal.archives-ouvertes.fr/lirmm-00906966