J. Han, J. Pei, B. Mortazavi-asl, Q. Chen, U. Dayal et al., FreeSpan, Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '00, pp.355-359, 2000.
DOI : 10.1145/347090.347167

J. Pei, J. Han, B. Mortazavi-asl, H. Pinto, Q. Chen et al., PrefixSpan Mining Sequential Patterns Efficiently by Prefix Projected Pattern Growth, 17th International Conference on Data Engineering, pp.215-226, 2001.

X. Yan, J. Han, and R. Afshar, CloSpan: Mining: Closed Sequential Patterns in Large Datasets, In: In SDM, pp.166-177, 2003.
DOI : 10.1137/1.9781611972733.15

B. Ding, D. Lo, J. Han, and S. C. Khoo, Efficient Mining of Closed Repetitive Gapped Subsequences from a Sequence Database, 2009 IEEE 25th International Conference on Data Engineering, pp.1024-1035, 2009.
DOI : 10.1109/ICDE.2009.104

C. Ra¨?ssira¨?ssi, T. Calders, and P. Poncelet, Mining conjunctive sequential patterns, Data Mining and Knowledge Discovery, vol.42, issue.1/2, pp.77-93, 2008.
DOI : 10.1007/s10618-008-0108-z

B. Ganter and R. Wille, Formal Concept Analysis: Mathematical Foundations, 1997.

B. Ganter and S. O. Kuznetsov, Pattern Structures and Their Projections, Conceptual Structures: Broadening the Base SE -10, pp.129-142, 2001.
DOI : 10.1007/3-540-44583-8_10
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.57.7648

M. Klimushkin, S. A. Obiedkov, and C. Roth, Approaches to the Selection of Relevant Concepts in the Case of Noisy Data, Proceedings of the 8th international conference on Formal Concept Analysis. ICFCA'10, pp.255-266, 2010.
DOI : 10.1007/978-3-642-11928-6_18

S. O. Kuznetsov, On stability of a formal concept, Annals of Mathematics and Artificial Intelligence, vol.8, issue.3, pp.101-115, 2007.
DOI : 10.1007/s10472-007-9053-6

G. Casas-garriga, Summarizing Sequential Data with Closed Partial Orders, In: SDM, 2005.
DOI : 10.1137/1.9781611972757.34
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.215.2604

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.1-37, 2010.
DOI : 10.1145/1644873.1644877
URL : https://hal.archives-ouvertes.fr/hal-01381826

S. Kuznetsov, Learning of Simple Conceptual Graphs from Positive and Negative Examples, LNCS, vol.1704, pp.384-391, 1999.
DOI : 10.1007/978-3-540-48247-5_47

D. V. Merwe, S. Obiedkov, and D. Kourie, AddIntent: A new incremental algorithm for constructing concept lattices, Concept Lattices, pp.372-385, 2004.

C. Roth, S. Obiedkov, and D. G. Kourie, ON SUCCINCT REPRESENTATION OF KNOWLEDGE COMMUNITY TAXONOMIES WITH FORMAL CONCEPT ANALYSIS, International Journal of Foundations of Computer Science, vol.19, issue.02, pp.383-404, 2008.
DOI : 10.1142/S0129054108005735

R. B. Fetter, Y. Shin, J. L. Freeman, R. F. Averill, and J. D. Thompson, Case mix definition by diagnosis-related groups, Med Care, vol.18, issue.2, pp.1-53, 1980.

R. 1. Carpineto, S. Osi´nskiosi´nski, G. Romano, and D. Weiss, A survey of Web clustering engines, ACM Computing Surveys, vol.41, issue.3, pp.1-38, 2009.
DOI : 10.1145/1541880.1541884

C. Carpineto and G. Romano, Order-theoretical ranking, Journal of the American Society for Information Science, vol.12, issue.7, pp.587-601, 2000.
DOI : 10.1002/(SICI)1097-4571(2000)51:7<587::AID-ASI2>3.0.CO;2-L
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.58.3770

C. Carpineto and G. Romano, Exploiting the potential of concept lattices for information retrieval with CREDO, Journal of Universal Computer Science, vol.10, pp.985-1013, 2004.

C. Carpineto and G. Romano, Using Concept Lattices for Text Retrieval and Mining. Formal Concept Analysis, pp.161-179, 2005.

V. Codocedo, I. Lykourentzou, and A. Napoli, Semantic querying of data guided by Formal Concept Analysis, Formal Concept Analysis for Artificial Intelligence Workshop at ECAI 2012, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00760757

S. Ferré, Camelis: a logical information system to organise and browse a collection of documents, International Journal of General Systems, vol.12, issue.4, pp.379-403, 2009.
DOI : 10.1016/S0169-023X(02)00057-5

B. Ganter and S. O. Kuznetsov, Pattern Structures and Their Projections, Conceptual Structures: Broadening the Base, 2001.
DOI : 10.1007/3-540-44583-8_10

B. Ganter and R. Wille, Formal Concept Analysis: Mathematical Foundations, 1999.

D. I. Ignatov and S. O. Kuznetsov, Concept-based Recommendations for Internet Advertisement, 2009.

M. Kaytoue, Z. Assaghir, A. Napoli, and S. O. Kuznetsov, Embedding tolerance relations in formal concept analysis, Proceedings of the 19th ACM international conference on Information and knowledge management, CIKM '10, p.1689, 2010.
DOI : 10.1145/1871437.1871705
URL : https://hal.archives-ouvertes.fr/inria-00600205

M. Kaytoue, S. O. Kuznetsov, and A. Napoli, Revisiting numerical pattern mining with formal concept analysis, Proceedings of the Twenty-Second international joint conference on Artificial Intelligence -Volume Volume Two, pp.1342-1347, 2011.
URL : https://hal.archives-ouvertes.fr/inria-00584371

S. O. Kuznetsov, Pattern Structures for Analyzing Complex Data, Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, pp.33-44, 2009.
DOI : 10.1007/978-3-642-10646-0_4

C. Manning, P. Raghavan, and H. Schütze, Introduction to Information Retrieval, 2009.
DOI : 10.1017/CBO9780511809071

N. Messai, M. Devignes, A. Napoli, and M. Sma¨?lsma¨?l-tabbone, Querying a Bioinformatic Data Sources Registry with Concept Lattices, Proceedings of the 13th international conference on Conceptual Structures: common Semantics for Sharing Knowledge, 2005.
DOI : 10.1007/11524564_22
URL : https://hal.archives-ouvertes.fr/inria-00000102

N. Messai, M. Devignes, A. Napoli, and M. Sma¨?lsma¨?l-tabbone, Using Domain Knowledge to Guide Lattice-based Complex Data Exploration, Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence, pp.847-852, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00545545

U. Priss, Lattice-based Information Retrieval, Knowledge Organization, vol.27, pp.132-142, 2000.

G. Salton, E. A. Fox, and H. Wu, Extended Boolean information retrieval, Communications of the ACM, vol.26, issue.11, pp.1022-1036, 1983.
DOI : 10.1145/182.358466
URL : http://ecommons.cornell.edu/bitstream/1813/6351/1/82-511.pdf

G. Stumme, R. Taouil, Y. Bastide, L. Lakhal, P. Hotho et al., Conceptual clustering with iceberg concept lattices Conceptual knowledge processing with formal concept analysis and ontologies, Proc. GI-Fachgruppentreffen Maschinelles Lernen Concept Lattices, pp.189-207, 2001.

A. Dogac, Y. Kabak, and G. B. Laleci, Enriching ebXML registries with OWL ontologies for efficient service discovery ., 14th International Workshop Research Issues on Data Engineering: Web Services for e-Commerce and e-Government Applications, 2004. Proceedings., 2004.
DOI : 10.1109/RIDE.2004.1281705

A. Gómez-pérez, O. Corcho, and M. Fernandez-lopez, Ontological Engineering, 2002.

J. E. Jridi and G. Lapalme, Adapting RosettaNet B2B standard to Semantic Web Technologies, 15th International Conference on Enterprise Information Systems, pp.484-491, 2013.

P. Kotinurmi, A. Haller, and E. Oren, Ontologically Enhanced RosettaNet B2B Integration, Semantic Web for Business: Cases and Applications, 2008.

P. Kotinurmi, A. Haller, and E. Oren, Global Business: Concepts, Methodologies, Tools and Application, Ontologically enhanced RosettaNet B2B Integration, p.27, 2011.

M. Lytras and R. García, Semantic Web applications: a framework for industry and business exploitation – What is needed for the adoption of the Semantic Web from the market and industry, International Journal of Knowledge and Learning, vol.4, issue.1, pp.93-108, 2008.
DOI : 10.1504/IJKL.2008.019739

M. Obitko, V. Snasel, J. Smid, and V. Snasel, Ontology design with formal concept analysis, Concept Lattices and their Applications, pp.111-119, 2004.

F. T. Sheldon, K. Jerath, and H. Chung, Metrics for maintainability of class inheritance hierarchies, Journal of Software Maintenance and Evolution: Research and Practice, vol.30, issue.3, pp.147-160, 2002.
DOI : 10.1002/smr.249

M. Sicilia, D. Rodríguez, E. García-barriocanal, and S. Sanchez-alonso, Empirical findings on ontology metrics, Expert Systems with Applications, vol.39, issue.8, pp.6706-6711, 2012.
DOI : 10.1016/j.eswa.2011.11.094

G. Stumme, Using Ontologies and Formal Concept Analysis for Organizing Business Knowledge, Proc. Referenzmodellierung, 2001.
DOI : 10.1007/978-3-642-52449-3_4

S. Tartir, I. B. Arpinar, M. Moore, A. P. Sheth, and B. Aleman-meza, OntoQA: Metric-based ontology quality analysis, IEEE Workshop on Knowledge Acquisition from Distributed, Autonomous, Semantically Heterogeneous Data and Knowledge Sources, 2005.

J. Wang, Y. P. Song, M. Cordero, A. Enciso, I. P. Mora et al., Architectures Supporting RosettaNet, Fourth International Conference on Software Engineering Research, Management and Applications (SERA'06), pp.31-39, 2002.
DOI : 10.1109/SERA.2006.18

P. Cordero, M. Enciso, A. Mora, and M. Ojeda-aciego, Computing minimal generators from implications: a logic-guided approach, Concept Lattice and Aplications, CLA, vol.2012, pp.187-198, 2012.

B. Ganter, Two Basic Algorithms in Concept Analysis, 1984.
DOI : 10.1007/978-3-642-11928-6_22

J. L. Guigues and V. Duquenne, Familles minimales d'implications informatives résultant d'un tableau de données binaires, Math. Sci. Humaines, vol.95, pp.5-18, 1986.

M. Hermann and B. Sertkaya, On the Complexity of Computing Generators of Closed Sets, pp.158-168, 2008.
DOI : 10.1007/978-3-540-78137-0_12

R. Hill, Computational Intelligence and Emerging Data Technologies, 2010 International Conference on Intelligent Networking and Collaborative Systems, pp.449-454, 2010.
DOI : 10.1109/INCOS.2010.94

A. Mora, P. Cordero, and M. , Enciso, I. Fortes, Closure via functional dependence simplification, IJCM, vol.89, issue.4, pp.510-526, 2012.

L. Szathmary, A. Napoli, and S. O. Kuznetsov, ZART: A Multifunctional Itemset Mining Algorithm, Proc. of the 6th Intl. Conf. on Concept Lattices and Their Applications (CLA '08), pp.47-58, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00189423

L. Szathmary, P. Valtchev, A. Napoli, and R. Godin, An Efficient Hybrid Algorithm for Mining Frequent Closures and Generators, Concept Lattices and Their Applications (CLA '07), pp.26-37, 2007.

R. Wille, Restructuring lattice theory: an approach based on hierarchies of concepts Ordered sets, pp.445-470, 1982.

A. Mikhail, S. O. Babin, and . Kuznetsov, Computing premises of a minimal cover of functional dependencies is intractable, Discrete Applied Mathematics, vol.161, issue.6, pp.742-749, 2013.

P. Cellier, M. Ducassé, S. Ferré, and O. Ridoux, Formal Concept Analysis Enhances Fault Localization in Software, Lecture Notes in Computer Science, vol.4933, pp.273-288, 2008.
DOI : 10.1007/978-3-540-78137-0_20
URL : https://hal.archives-ouvertes.fr/inria-00363593

H. Cleve and A. Zeller, Locating causes of program failures, pp.342-351, 2005.

F. Distel and B. Sertkaya, On the complexity of enumerating pseudo-intents, Discrete Applied Mathematics, vol.159, issue.6, pp.450-466, 2011.
DOI : 10.1016/j.dam.2010.12.004

B. Ganter, Two Basic Algorithms in Concept Analysis, 1984.
DOI : 10.1007/978-3-642-11928-6_22

B. Ganter, G. Stumme, and R. Wille, Formal Concept Analysis , Foundations and Applications, Lecture Notes in Computer Science, vol.3626, 2005.

B. Ganter and R. Wille, Formal Concept Analysis: Mathematical Foundations, 1999.

M. Gerndt, Towards automatic performance debugging tools, AADEBUG, 2000.

R. Godin and P. Valtchev, Formal Concept Analysis-Based Class Hierarchy Design in Object-Oriented Software Development, Ganter et al. [7], pp.304-323
DOI : 10.1007/11528784_16

J. Guigues and V. Duquenne, Familles minimales d'implications informatives résultant d'un tableau de données binaires, Math. Sci. Hum, vol.24, issue.95, pp.5-18, 1986.

O. Sergei, S. A. Kuznetsov, and . Obiedkov, Some decision and counting problems of the duquenne-guigues basis of implications, Discrete Applied Mathematics, vol.156, issue.11, pp.1994-2003, 2008.

L. John and . Pfaltz, Using concept lattices to uncover causal dependencies in software, Proc. Int. Conf. on Formal Concept Analysis, pp.233-247, 2006.

A. Revenko and S. O. Kuznetsov, Finding errors in new object intents, CLA 2012, pp.151-162, 2012.

U. Ryssel, F. Distel, and D. Borchmann, Fast computation of proper premises, International Conference on Concept Lattices and Their Applications, pp.101-113, 2011.

G. Snelting and F. Tip, Reengineering class hierarchies using concept analysis, ACM SIGSOFT Software Engineering Notes, vol.23, issue.6, pp.99-110, 1998.
DOI : 10.1145/291252.288273

A. Zeller and R. Hildebrandt, Simplifying and isolating failure-inducing input, IEEE Transactions on Software Engineering, vol.28, issue.2, pp.183-200, 2002.
DOI : 10.1109/32.988498

A. A. Neznanov, D. A. Ilvovsky, and S. O. Kuznetsov, FCART: A New FCA-based System for Data Analysis and Knowledge Discovery, Proc. of workshop for FCA Tools and Applications, 2013.

S. Kuznetsov, Fitting Pattern Structures to Knowledge Discovery in Big Data, Lecture Notes in Computer Science, vol.7880, pp.254-266, 2013.
DOI : 10.1007/978-3-642-38317-5_17

B. Ganter and R. Wille, Formal Concept Analysis: Mathematical Foundations, 1997.

M. Kaytoue, S. O. Kuznetsov, A. Napoli, and S. Duplessis, Mining gene expression data with pattern structures in formal concept analysis, Information Sciences, vol.181, issue.10, pp.1989-2001, 2011.
DOI : 10.1016/j.ins.2010.07.007
URL : https://hal.archives-ouvertes.fr/hal-00541100

S. O. Kuznetsov, A fast algorithm for computing all intersections of objects in a finite semi-lattice, Automatic documentation and Mathematical linguistics, vol.27, issue.5, pp.11-21, 1993.

D. V. Merwe, S. Obiedkov, and D. Kourie, AddIntent: A new incremental algorithm for constructing concept lattices, Concept Lattices, pp.372-385, 2004.