Mining sequential patterns, Proceedings of the Eleventh International Conference on Data Engineering, pp.3-14, 1995. ,
DOI : 10.1109/ICDE.1995.380415
Summarizing Sequential Data with Closed Partial Orders, 2005 SIAM Int. Conference on Data Mining, pp.380-391, 2005. ,
DOI : 10.1137/1.9781611972757.34
A contribution to the discovery of multidimensional patterns in healthcare trajectories, Journal of Intelligent Information Systems, vol.42, issue.1???2, pp.283-305, 2014. ,
DOI : 10.1023/A:1007652502315
URL : https://hal.archives-ouvertes.fr/hal-01094377
, 60/ec of the European parliament and of the council of 23 october 2000 establishing a framework for community action in the field of water policy, Official Journal OJ L, vol.327, pp.1-73, 2000.
Formal Concept Analysis: Mathematical Foundations, 1999. ,
Exploring temporal data using relational concept analysis: An application to hydroecological data, Proceedings of the 13th Int. Conf. on Concept Lattices and Their Applications, pp.299-311, 2016. ,
Extracting Hierarchies of Closed Partially-Ordered Patterns Using Relational Concept Analysis, Graph- Based Representation and Reasoning: 22nd Int. Conf. on Conceptual Structures, ICCS 2016, Proceedings. pp, pp.17-30, 2016. ,
DOI : 10.1007/978-3-540-88192-6_68
URL : https://hal.archives-ouvertes.fr/hal-01380407
Prefixspan: Mining sequential patterns efficiently by prefix-projected pattern growth, Proceedings of the 17th Int. Conf. on Data Engineering, pp.215-224, 2001. ,
Multi-dimensional sequential pattern mining, Proceedings of the tenth international conference on Information and knowledge management , CIKM'01, pp.81-88, 2001. ,
DOI : 10.1145/502585.502600
Mining multidimensional and multilevel sequential patterns, ACM Transactions on Knowledge Discovery from Data, vol.4, issue.1, pp.1-4, 2010. ,
DOI : 10.1145/1644873.1644877
URL : https://hal.archives-ouvertes.fr/hal-01381826
Impact of Physico-Chemical Parameters on Microbial Diversity: Seasonal Study, Current World Environment, vol.6, issue.1, pp.71-76, 2011. ,
DOI : 10.12944/CWE.6.1.09
Relational concept analysis: mining concept lattices from multi-relational data, Annals of Mathematics and Artificial Intelligence, vol.5, issue.1, pp.81-108, 2013. ,
DOI : 10.1007/978-94-009-7798-3_15
URL : https://hal.archives-ouvertes.fr/lirmm-00816300
Mining sequential patterns: Generalizations and performance improvements, Proceedings of the 5th Int. Conf. on Extending DB Technology: Advances in DB Technology, pp.3-17, 1996. ,
DOI : 10.1007/BFb0014140
URL : http://arbor.ee.ntu.edu.tw/~chyun/dmpaper/srikms96.pdf
Can we predict biological condition of stream ecosystems? A multi-stressors approach linking three biological indices to physico-chemistry, hydromorphology and land use, Ecological Indicators, vol.48, pp.88-98, 2015. ,
DOI : 10.1016/j.ecolind.2014.07.016
URL : https://hal.archives-ouvertes.fr/hal-01249371
Quelle limite de " bonétatécologiquebonétatbonétatécologique " pour les invertébrés benthiques enrivì eres ? Apport des modèles d'extrapolation spatiale reliant l'indice biologique global normalisénormalisé`normaliséà l'occupation du sol, Ingénieries -E A T, vol.1, issue.47, pp.3-15, 2006. ,
Spade: An efficient algorithm for mining frequent sequences, Machine Learning, vol.42, issue.1/2, pp.31-60, 2001. ,
DOI : 10.1023/A:1007652502315