R. Agrawal, T. Imielinski, and A. Swami, Mining Association Rules between Sets of Items in Large Databases, Proceedings, ACM SIGMOD Conference on Management of Data, pp.207-216, 1993.

R. Agrawal, H. Mannila, R. Srikant, H. Toivonen, and A. I. Verkamo, Fast Discovery of Association Rules, Advances in Knowledge Discovery and Data Mining, pp.307-328, 1996.

R. Agrawal and R. Srikant, Fast algorithms for mining association rules in large databases, Proceedings of the 20th Conference on Very Large Data Bases (VLDB-94), pp.478-499, 1994.

M. Barbut and B. Monjardet, Ordre et classification ? Algèbre et combinatoire (2 tomes), 1970.

S. Berasaluce, C. Laurenço, A. Napoli, and G. Niel, An Experiment on Knowledge Discovery in Chemical Databases, Knowledge Discovery in Databases: PKDD 2004, pp.39-51, 2004.
DOI : 10.1007/978-3-540-30116-5_7
URL : https://hal.archives-ouvertes.fr/inria-00100272

S. Berasaluce, C. Laurenço, A. Napoli, and G. Niel, Data mining in reaction databases: extraction of knowledge on chemical functionality transformations, 2004.
URL : https://hal.archives-ouvertes.fr/inria-00099862

B. Berendt, A. Hotho, and G. Stumme, Towards Semantic Web Mining, Lecture Notes in Artificial Intelligence, vol.2342, pp.264-278, 2002.
DOI : 10.1007/3-540-48005-6_21
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.123.2066

R. J. Brachman and T. Anand, The Process of Knowledge Discovery in Databases, Advances in Knowledge Discovery and Data Mining, pp.37-57, 1996.

C. Carpineto and G. Romano, Concept Data Analysis: Theory and Applications, 2004.
DOI : 10.1002/0470011297

H. Cherfi, A. Napoli, and Y. Toussaint, Toward a text mining methodology using frequent itemset and association rule extraction, Journées de l'informatique Messine (JIM- 2003), Knowledge Discovery and Discrete Mathematics, pp.285-294, 2003.

C. Creighton and S. Hanash, Mining gene expression databases for association rules, Bioinformatics, vol.19, issue.1, pp.79-86, 2003.
DOI : 10.1093/bioinformatics/19.1.79

B. A. Davey and H. A. Priestley, Introduction to Lattices and Order, 1990.
DOI : 10.1017/CBO9780511809088

L. Dehaspe and H. Toivonen, Discovery of frequent datalog patterns, Data Mining and Knowledge Discovery, vol.3, issue.1, pp.7-36, 1999.
DOI : 10.1023/A:1009863704807

M. H. Dunham, Data Mining ? Introductory and Advanced Topics, 2003.

V. Duquenne, Latticial structures in data analysis, Theoretical Computer Science, vol.217, issue.2, pp.407-436, 1999.
DOI : 10.1016/S0304-3975(98)00279-5

U. M. Fayyad, G. Piatetsky-shapiro, P. Smyth, and R. Uthurusamy, Advances in Knowledge Discovery and Data Mining, 1996.

B. Ganter, P. A. Grigoriev, S. O. Kuznetsov, and M. V. Samokhin, Concept-Based Data Mining with Scaled Labeled Graphs, Conceptual Structures at Work: Proceedings of the 12th International Conference on Conceptual Structures, pp.94-108, 2004.
DOI : 10.1007/978-3-540-27769-9_6

B. Ganter and S. Rudolph, Formal Concept Analysis Methods for Dynamic Conceptual Graphs, Conceptual Structures: Broadening the Base ? 9th International Conference on Conceptual Structures, ICCS-2001, pp.143-156, 2001.
DOI : 10.1007/3-540-44583-8_11

B. Ganter and R. Wille, Formal Concept Analysis, 1999.

A. Guénoche and I. Van-mechelen, Galois Approach to the Induction of Concepts, Categories and Concepts. Theoretical Views and Inductive Data Analysis, pp.287-308, 1993.

J. Han and M. Kamber, Data Mining, 2001.
DOI : 10.1007/978-1-4899-7993-3_104-2

D. Hand, H. Mannila, and P. Smyth, Principles of Data Mining, Drug Safety, vol.15, issue.2, 2001.
DOI : 10.2165/00002018-200730070-00010

D. Janetzko, H. Cherfi, R. Kennke, A. Napoli, and Y. Toussaint, Knowledgebased selection of association rules for text mining, 16h European Conference on Artificial Intelligence ? ECAI'04, pp.485-489, 2004.
URL : https://hal.archives-ouvertes.fr/inria-00107787

R. Kosala and H. Blockeel, Web Mining: A Survey, SIGKDD Explorations, pp.1-15, 2000.

S. O. Kuznetsov, Machine Learning and Formal Concept Analysis, Concept Lattices, Second International Conference on Formal Concept Analysis, pp.287-312, 2004.
DOI : 10.1007/978-3-540-24651-0_25

S. O. Kuznetsov and S. A. Obiedkov, Algorithms for the Construction of Concept Lattices and Their Diagram Graphs, Principles of Data Mining and Knowledge Discovery: 5th European Conference, pp.289-300, 2001.
DOI : 10.1007/3-540-44794-6_24

S. O. Kuznetsov and S. A. Obiedkov, Comparing performance of algorithms for generating concept lattices, Journal of Experimental & Theoretical Artificial Intelligence, vol.21, issue.2-3, pp.189-216, 2002.
DOI : 10.1016/S0020-0190(99)00108-8

N. Lavrac, P. A. Flach, and B. Zupan, Rule Evaluation Measures: A Unifying View, Inductive Logic Programming, 9th International Workshop, ILP-99, pp.174-185, 1999.
DOI : 10.1007/3-540-48751-4_17

H. Mannila, Methods and problems in data mining, Database Theory ? ICDT'97 6th International Conference, pp.41-55, 1997.
DOI : 10.1007/3-540-62222-5_35

H. Mannila, H. Toivonen, and A. I. Verkamo, Efficient algorithms for discovering association rules, Proceedings of the 1994 Knowledge Discovery in Databases Workshop, KDD'94, pp.181-192, 1994.

T. M. Mitchell, Machine Learning, 1997.

A. Napoli, C. Laurenço, and R. Ducournau, An object-based representation system for organic synthesis planning, International Journal of Human-Computer Studies, vol.41, issue.1-2, pp.5-32, 1994.
DOI : 10.1006/ijhc.1994.1051

N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal, Discovering Frequent Closed Itemsets for Association Rules, Database Theory -ICDT'99 Proceedings, 7th International Conference, pp.398-416, 1999.
DOI : 10.1007/3-540-49257-7_25
URL : https://hal.archives-ouvertes.fr/hal-00467747

N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal, Pruning closed itemset lattices for association rules, International Journal of Information Systems, vol.24, issue.1, pp.25-46, 1999.
URL : https://hal.archives-ouvertes.fr/hal-00467745

G. Schreiber, H. Akkermans, A. Anjewierden, R. De-hoog, N. Shadbolt et al., Knowledge Engineering and Management: the CommonKADS Methodoloy, 1999.

G. Stumme, R. Taouil, Y. Bastide, N. Pasquier, and L. Lakhal, Computing iceberg concept lattices with Titanic, Data & Knowledge Engineering, vol.42, issue.2, pp.189-222, 2002.
DOI : 10.1016/S0169-023X(02)00057-5
URL : https://hal.archives-ouvertes.fr/hal-00578830

G. Stumme, R. Wille, and U. Wille, Conceptual Knowledge Discovery in Databases using formal concept analysis methods, Principles of Data Mining and Knowledge Discovery (Proceedings PKDD'98, Nantes), pp.450-458, 1510.
DOI : 10.1007/BFb0094849

P. N. Tan, V. Kumar, and J. Srivastava, Selecting the right interestingness measure for association patterns, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '02, pp.183-193, 2002.
DOI : 10.1145/775047.775053

P. Valtchev, R. Missaoui, and R. Godin, Formal Concept Analysis for Knowledge Discovery and Data Mining: The New Challenges, Concept Lattices, Second International Conference on Formal Concept Analysis, pp.352-371, 2004.
DOI : 10.1007/978-3-540-24651-0_30

P. Vismara and C. Laurenço, An abstract representation for molecular graphs. DI- MACS Series in Discrete Mathematics and Theoretical Computer Science, pp.343-366, 2000.

R. Wille, Why can concept lattices support knowledge discovery in databases?, Journal of Experimental & Theoretical Artificial Intelligence, vol.14, issue.2-3, pp.81-92, 2002.
DOI : 10.1007/s002870000127

I. H. Witten and E. Franck, Data mining, Practical machine learning tools and techniques with Java implementations ? Weka), 2000.
DOI : 10.1145/507338.507355

M. J. Zaki and C. Hsiao, CHARM: An Efficient Algorithm for Closed Itemset Mining, Second SIAM International Conference on Data Mining, 2002.
DOI : 10.1137/1.9781611972726.27