R. Agrawal and R. Srikant, Fast algorithms for mining association rules, The International Conference on Very Large Databases, VLDB, pp.487-499, 1994.

C. Anderson, The Long Tail: Why the Future of Business Is Selling Less of More, 2006.

Z. K. Baker and V. K. Prasanna, Eff cient hardware data mining with the Apriori algorithm on FPGAs, 13th Annual IEEE Symposium on Field-Programmable Custom Computing Machines, pp.3-12, 2005.

Z. K. Baker and V. K. Prasanna, An Architecture for Eff cient Hardware Data Mining using Reconf gurable Computing Systems, 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines, pp.67-75, 2006.
DOI : 10.1109/fccm.2006.22
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.106.771

C. Borgelt, Eff cient implementations of apriori and eclat, Proceedings of the IEEE ICDM workshop on frequent itemset mining implementations, 2003.

L. Bustio, R. Cumplido, R. Hernández, J. M. Bande, and C. Feregrino, New Frontiers in Mining Complex Patterns: 4th International Workshop, NFMCP 2015, Chapter Frequent Itemsets Mining in Data Streams Using Reconf gurable Hardware, pp.32-45, 2016.

O. Cret, Z. Mathe, P. Ciobanu, S. Marginean, and A. Darabant, A hardware algorithm for the exact subsequence matching problem in DNA strings, Romanian Journal of Information Science and Technology, vol.12, issue.1, pp.51-67, 2009.

F. Repository, /. Gu, Y. Zhu, S. Zhou, C. Wang et al., Frequent Itemset Mining Dataset Repository A Real-Time FPGA- Based Accelerator for ECG Analysis and Diagnosis Using Association-Rule Mining, ACM Transactions on Embedded Computing Systems, vol.15, issue.2, p.25, 2003.

J. Han, J. Pei, and Y. Yin, Mining frequent patterns without candidate generation, ACM SIGMOD Record, vol.29, issue.2, pp.1-12, 2000.
DOI : 10.1145/335191.335372
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.35.2678

M. Jacobsen, D. Richmond, M. Hogains, and R. Kastner, RIFFA 2.1, ACM Transactions on Reconfigurable Technology and Systems, vol.8, issue.4, 2015.
DOI : 10.1145/2815631

I. Micron, Micron Automata Developer Portal -Hardware, 2016.

V. B. Nikam and B. B. Meshram, Scalable Frequent Itemset Mining Using Heterogeneous Computing : Parapriori Algorithm, International Journal of Distributed and Parallel systems, vol.5, issue.5, p.13, 2014.
DOI : 10.5121/ijdps.2014.5502

S. Shi, Y. Qi, and Q. Wang, FPGA Acceleration for Intersection Computation in Frequent Itemset Mining, 2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, pp.514-519, 2013.
DOI : 10.1109/CyberC.2013.95

S. Sun, M. Steffen, and J. Zambreno, A Reconf gurable Platform for Frequent Pattern Mining, International Conference on Reconf gurable Computing and FPGAs, pp.55-60, 2008.

S. Sun and J. Zambreno, Design and Analysis of a Reconfigurable Platform for Frequent Pattern Mining, IEEE Transactions on Parallel and Distributed Systems, vol.22, issue.9, pp.1497-1505, 2011.
DOI : 10.1109/TPDS.2011.34

D. Thoni and A. Strey, Novel strategies for hardware acceleration of frequent itemset mining with the apriori algorithm, 2009 International Conference on Field Programmable Logic and Applications, 2009.
DOI : 10.1109/FPL.2009.5272494

T. Uno, T. Asai, Y. Uchida, and H. Arimura, LCM: An Eff cient Algorithm for Enumerating Frequent Closed Item Sets, Proceedings of the IEEE ICDM workshop on frequent itemset mining implementations, 2003.

T. Uno, M. Kiyomi, and H. Arimura, LCM ver.3, Proceedings of the 1st international workshop on open source data mining frequent pattern mining implementations, OSDM '05, pp.77-86, 2005.
DOI : 10.1145/1133905.1133916

K. Wang, Y. Qi, J. J. Fox, M. R. Stan, and K. Skadron, Association Rule Mining with the Micron Automata Processor, 2015 IEEE International Parallel and Distributed Processing Symposium, pp.689-699, 2015.
DOI : 10.1109/IPDPS.2015.101

Y. Wen, J. Huang, and M. Chen, Hardware-Enhanced Association Rule Mining with Hashing and Pipelining, IEEE Transactions on Knowledge and Data Engineering, vol.20, issue.6, pp.784-795, 2008.

X. Inc, Device Reliability Report -First Half 2015, 2015.

O. Zaiane, Rich Data: Risks, Issues, Controversies & Hype, dec. 2014). Keynote speech at the International Conference on Advanced Data Mining and Applications, 2014.

J. Mohammed and . Zaki, Scalable Algorithms for Association Mining, IEEE Transactions on Knowledge and Data Engineering, vol.12, issue.3, pp.372-390, 2000.

M. J. Zaki, M. S. Parthasarathy, W. Ogihara, and . Li, New Algorithms for Fast Discovery of Association Rules, 3rd International Conference on Knowledge Discovery and Data Mining, pp.283-286, 1997.

F. Zhang, Y. Zhang, and J. D. Bakos, Accelerating frequent itemset mining on graphics processing units, The Journal of Supercomputing, vol.8, issue.1, pp.94-117, 2013.
DOI : 10.1007/s11227-013-0887-x
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.434.1906

Y. Zhang, F. Zhang, Z. Jin, and J. D. Bakos, An FPGA-Based Accelerator for Frequent Itemset Mining, ACM Transactions on Reconfigurable Technology and Systems, vol.6, issue.1, p.17, 2013.
DOI : 10.1145/2457443.2457445
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.307.6859