J. Ayres, J. Flannick, J. Gehrke, and T. Yiu, Sequential PAttern mining using a bitmap representation, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '02
DOI : 10.1145/775047.775109
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.5575

D. Chiu, Y. Wu, and A. L. Chen, An efficient algorithm for mining frequent sequences by a new strategy without support counting, ICDE, pp.375-386, 2004.

J. Cohen, J. Eshleman, B. Hagenbuch, J. Kent, C. Pedrotti et al., Online expansion of largescale data warehouses, PVLDB, vol.4, issue.1 2

F. Masseglia, F. Cathala, and P. Poncelet, The PSP approach for mining sequential patterns, PKDD
DOI : 10.1007/BFb0094818

J. Pei, J. Han, B. Mortazavi-asl, H. Pinto, Q. Chen et al., Prefixspan: Mining sequential patterns by prefixprojected growth, ICDE

M. Plantevit, A. Laurent, D. Laurent, M. Teisseire, and Y. W. Choong, Mining multidimensional and multilevel sequential patterns, ACM Transactions on Knowledge Discovery from Data, vol.4, issue.1, pp.1-3
DOI : 10.1145/1644873.1644877
URL : https://hal.archives-ouvertes.fr/hal-01381826

E. Salvemini, F. Fumarola, D. Malerba, and J. Han, FAST Sequence Mining Based on Sparse Id-Lists, Proceedings of the 19th international conference on Foundations of intelligent systems, pp.316-325, 2011.
DOI : 10.1007/978-3-540-88636-5_72

X. Yan, J. Han, and R. Afshar, CloSpan: Mining: Closed Sequential Patterns in Large Datasets, SDM
DOI : 10.1137/1.9781611972733.15
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.3538

Z. Yang, M. Kitsuregawa, and Y. Wang, PAID: Mining Sequential Patterns by Passed Item Deduction in Large Databases, 2006 10th International Database Engineering and Applications Symposium (IDEAS'06), 2006.
DOI : 10.1109/IDEAS.2006.34
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.330.6548

C. Yu and Y. Chen, Mining sequential patterns from multidimensional sequence data, IEEE Trans. Knowl. Data Eng, vol.7, issue.1 1

J. Mohammed and . Zaki, Spade: An efficient algorithm for mining frequent sequences, Mach. Learn, vol.42, issue.12, pp.31-60, 2001.

C. Zhang, K. Hu, Z. Chen, L. Chen, and Y. Dong, ApproxMGMSP: A Scalable Method of Mining Approximate Multidimensional Sequential Patterns on Distributed System, Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)
DOI : 10.1109/FSKD.2007.192