C. , Data Streams: Models and Algorithms, 2007.

N. Alon, Y. Matias, and M. Szegedy, The space complexity of approximating the frequency moments, Proc. of the 28th annual ACM Symposium on Theory of Computing (STOC'96), pp.20-29, 1996.

F. Berzal, J. Cubero, D. Sanchez, M. Vila, and J. Serrano, An alternative approach to discover gradual dependencies, Fuzziness and Knowledge-Based Systems (IJUFKS), vol.15, pp.559-570, 2007.

B. H. Bloom, Space/time trade-offs in hash coding with allowable errors, Communications of the ACM, vol.13, issue.7, pp.422-426, 1970.

T. Calders, N. Dexters, and B. Goethals, Mining frequent itemsets in a stream, Proc. of the IEEE Int. Conference on Data Mining (ICDM'07), pp.83-92, 2007.

T. Calders, N. Dexters, and B. Goethals, Mining frequent items in a stream using flexible windows, Journal of Intelligent Data Analysis, vol.12, issue.3, pp.293-304, 2008.

M. Charikar, K. Chen, and M. Farach-colton, Finding frequent items in data streams, Theoretical Computer Sciences, vol.312, issue.1, pp.3-15, 2004.

Y. Chi, H. Wang, P. Yu, and R. Muntz, Moment: Maintaining closed frequent itemsets over a stream sliding window, Proc. of the IEEE Int. Conference on Data Mining (ICDM'04), 2004.

F. Coenen, G. Goulbourne, and P. Leng, Tree structures for mining association rules, Data Mining and Knowledge Discovery, vol.8, issue.1, pp.25-51, 2004.

G. Giannella, J. Han, J. Pei, X. Yan, and P. Yu, Mining frequent patterns in data streams at multiple time granularities, Next Generation Data Mining, 2003.

S. Greco, B. Matarazzo, N. Pappalardo, and R. Slowinski, Measuring expected effects of interventions based on decision rules, Journal of Experimental and Theoretical Artificial Intelligence, vol.17, issue.1-2, 2006.

M. Greenwa and S. Khanna, Space-efficient online computation of quantile summaries, Proc. of the ACM Int. Conference on Management of data (SIGMOD'01), pp.56-66, 2001.

J. Han, Y. Chen, G. Dong, J. Pei, B. Wah et al., Stream cube: An architecture for multi-dimensional analysis of data streams. Distributed and Parallel Databases, vol.18, pp.173-197, 2005.

J. Han, J. Pei, B. Mortazavi-asl, Q. Chen, U. Dayal et al., Freespan: Frequent pattern-projected sequential pattern mining, Proc. of ACM Int. Conference on Knowledge Discovery and Data Mining (KDD'00), 2000.

J. Han, J. Pei, Y. Yin, and R. Mao, Mining frequent patterns without candidate generation, Data Mining and Knowledge Discovery, vol.8, pp.53-87, 2004.

E. Hüllermeier, Association rules for expressing gradual dependences, Proc. of the 6th Eu. Conf. on Principles of Data Mining and Knowledge Discovery (PKDD'02), pp.200-211, 2002.

L. D. Jorio, A. Laurent, and M. Teisseire, Fast extraction of gradual association rules: A heuristic based method, IEEE/ACM Int. Conference on Soft Computing as Transdisciplinary Science and Technology (CSTST), 2008.
URL : https://hal.archives-ouvertes.fr/lirmm-00324473

L. D. Jorio, A. Laurent, and M. Teisseire, Mining for gradualness over time using sequential patterns, Intelligent Decision Technologies (IDT'09), 2009.
URL : https://hal.archives-ouvertes.fr/lirmm-00362568

H. Li, S. Lee, and M. Shan, An efficient algorithm for mining frequent itemsets over the entire history of data streams, Proc. of 1st Int. Workshop on Knowledge Discovery in Data Streams, 2004.

G. Manku and R. Motwani, Approximate frequency counts over data streams, Proc.of 28th Int. Conf. Very Large Databases, 2002.

F. Masseglia, P. Poncelet, M. Teisseire, and A. Marascu, Web usage mining: extracting unexpected periods from web logs. Data Mining and Knowledge Discover, vol.16, pp.39-65, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00461877

R. J. Miller and Y. Yang, Association rules over interval data, SIGMOD '97: Proceedings of the 1997 ACM SIGMOD international conference on Management of data, pp.452-461, 1997.

B. Nag, P. M. Deshpande, and D. J. Dewitt, Using a knowledge cache for interactive discovery of association rules, KDD '99: Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, pp.244-253, 1999.

C. Raissi, P. Poncelet, and M. Teisseire, Speed : Mining maximal sequential patterns over data streams, Proc. of the 3rd IEEE Int. Conference On Intelligent Systems (IS2006), 2006.

C. Ra¨?ssira¨?ssi, P. Poncelet, and M. Teisseire, Towards a new approach for mining maximal frequent itemsets over data stream, Journal of Intelligent Information Systems, vol.28, issue.1, pp.23-36, 2007.

Z. Ras and A. Wieczorkowska, Action rules: how to increase profit of a company, Proceedings of the Principles of Data Mining and Knowledge Discovery (PKDD 00), pp.587-592, 2000.

A. Skowron and P. Synak, Planning based on reasoning about information changes, Rough Sets and Current Trends in Computing), pp.165-173, 2006.

E. J. Stollnitz, T. D. Derose, and D. H. Salesin, Wavelets for computer graphics: theory and applications, 1996.

W. Teng, M. Chen, and P. Yu, A regression-based temporal patterns mining schema for data streams, Proc. of 29th Int. Conf. Very Large Databases (VLDB'03), pp.93-104, 2003.

V. Torra, The weighted owa operator, Int. Journal of Intelligent Systems, vol.12, pp.153-166, 1997.

V. Torra, Owa operators in data modeling and re-identification, IEEE Trans. on Fuzzy Systems, vol.12, issue.5, pp.652-660, 2004.

V. Torra and Y. Narukawa, Modeling decisions: information fusion and aggregation operators, 2007.

V. Torra and J. Nin, Record linkage for database integration using fuzzy integrals, Int. Journal of Intelligent Systems, vol.23, issue.6, pp.715-734, 2008.

L. Tsay and Z. Ras, Action rules discovery system dear, method and experiments, Journal of Experimental and Theoretical Artificial Intelligence, vol.17, issue.1-2, pp.119-128, 2005.

A. Tzacheva and Z. Ras, Action rules mining, International Journal of Intelligent Systems, vol.20, issue.7, pp.719-736, 2005.

K. Verma, O. Vyas, and R. Vyas, Temporal approach to association rule mining using t-tree and p-tree, Machine Learning and Data Mining in Pattern Recognition, vol.3587, pp.651-659, 2005.

J. S. Vitter, Random sampling with a reservoir, ACM Transactions on Mathematical Software, vol.11, issue.1, pp.37-57, 1985.

R. R. Yager, On ordered weighted averaging aggregation operators in multi-criteria decision making, IEEE Trans. on Systems, Man and Cybernetics, vol.18, pp.183-190, 1988.

R. R. Yager, Families of owa operators. Fuzzy Sets and Systems, vol.59, pp.125-148, 1993.