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.

F. Baader, D. Calvanese, D. Mcguinness, D. Nardi, and P. Patel-schneider, The Description Logic Handbook, 2003.
DOI : 10.1017/CBO9780511711787

Y. Bastide, R. Taouil, N. Pasquier, G. Stumme, and L. Lakhal, Mining frequent patterns with counting inference, SIGKDD Exploration Newsletter, pp.66-75, 2000.
DOI : 10.1145/380995.381017

URL : https://hal.archives-ouvertes.fr/hal-00467750

R. Bendaoud, A. Napoli, and Y. Toussaint, Formal Concept Analysis: A Unified Framework for Building and Refining Ontologies, Knowledge Engineering: Practice and Patterns ? Proceedings of the 16th International Conference EKAW, pp.156-171, 2008.
DOI : 10.1007/978-3-540-87696-0_16

URL : https://hal.archives-ouvertes.fr/inria-00344051

R. Bendaoud, Y. Toussaint, and A. Napoli, PACTOLE: A Methodology and a System for Semi-automatically Enriching an Ontology from a Collection of Texts, Proceedings of the 16th International Conference on Conceptual Structures, pp.203-216, 2008.
DOI : 10.1007/978-3-540-70596-3_14

URL : https://hal.archives-ouvertes.fr/inria-00315530

D. P. Thierry-bertin-mahieux, B. Ellis, P. Whitman, and . Lamere, The million song dataset, Proceedings of the 12th International Conference on Music Information Retrieval, 2011.

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

D. Byrd and T. Crawford, Problems of music information retrieval in the real world, Information Processing and Management, pp.249-272, 2002.
DOI : 10.1016/S0306-4573(01)00033-4

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

M. D. 'aquin, F. Badra, S. Lafrogne, J. Lieber, A. Napoli et al., Case base mining for adaptation knowledge acquisition, pp.750-755, 2007.
URL : https://hal.archives-ouvertes.fr/inria-00127347

B. Diaz-agudo and P. A. Gonzales-calero, Formal Concept Analysis as a support technique for CBR. Knowledge-Based Systems, pp.163-171, 2001.

Z. Fu, G. Lu, K. M. Ting, and D. Zhang, A survey of audio-based music classification and annotation. Multimedia, IEEE Transactions on, vol.13, issue.2, pp.303-319, 2011.

B. Ganter and S. O. Kuznetsov, Pattern Structures and Their Projections, Conceptual Structures: Broadening the Base, Proceedings of the 9th International Conference on Conceptual Structures LNCS 2120, pp.129-142, 2001.
DOI : 10.1007/3-540-44583-8_10

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

X. Hu, J. Stephen-downie, and A. F. Ehmann, Lyric Text Mining in Music Mood Classification, 10th International Society for Music Information Retrieval Conference, pp.411-416, 2009.

M. Kaytoue, Z. Assaghir, N. Messai, and A. Napoli, Two Complementary Classication Methods for Designing a Concept Lattice from Interval Data, Sixth International Symposium on Foundations of Information and Knowledge Systems (FoIKS), pp.345-362, 2010.

M. Kaytoue-uberall, S. Duplessis, S. Kuznetsov, and A. Napoli, Two FCA-Based Methods for Mining Gene Expression Data, Proceedings of the 7th International Conference on Formal Concept Analysis LNAI 5548, pp.251-266, 2009.

A. Kiryakov, B. Popov, I. Terziev, D. Manov, and D. Ognyanoff, Semantic annotation, indexing, and retrieval, Web Semantics: Science , Services and Agents on the World Wide Web, pp.49-79, 2004.

M. Kuuskankare and M. Laurson, Mir in enp -rule-based music information retrieval from symbolic music notation, Proceedings of the 10th International Society for Music Information Retrieval Conference Kobe International Conference Center International Society for Music Information Retrieval, pp.699-704, 2009.

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

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

S. O. Kuznetsov and M. V. Samokhin, Learning Closed Sets of Labeled Graphs for Chemical Applications, Proceedings of 15th International Conference on Inductive Logic Programming (ILP 2005), pp.190-208, 2005.
DOI : 10.1007/11536314_12

C. Laurier, J. Grivolla, and P. Herrera, Multimodal Music Mood Classification Using Audio and Lyrics, 2008 Seventh International Conference on Machine Learning and Applications, 2008.
DOI : 10.1109/ICMLA.2008.96

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.182.426

J. Ha, L. , and J. Stephen-downie, Survey of music information needs, uses, and seeking behaviours: Preliminary findings, ISMIR Proceedings, pp.441-446, 2004.

J. Lieber, A. Napoli, L. Szathmary, and Y. Toussaint, First Elements on Knowledge Discovery Guided by Domain Knowledge (KDDK), Concept Lattices and Their Applications (CLA 06), LNAI 4923, pp.22-41, 2008.
DOI : 10.1007/978-3-540-78921-5_2

URL : https://hal.archives-ouvertes.fr/hal-00608015

B. Logan, A. Kositsky, and P. Moreno, Semantic analysis of song lyrics, 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763), pp.827-830, 2004.
DOI : 10.1109/ICME.2004.1394328

P. Lops, M. Gemmis, and G. Semeraro, Content-based Recommender Systems: State of the Art and Trends, Recommender Systems Handbook, pp.73-105, 2011.
DOI : 10.1007/978-0-387-85820-3_3

D. Christopher, H. Manning, and . Schütze, Foundations of Statistical Natural Language Processing, 1999.

L. Balby, M. , and L. Schmidt-thieme, Collaborative tag recommendations In Data Analysis, Machine Learning and Applications, Studies in Classification , Data Analysis, and Knowledge Organization, pp.533-540, 2008.

N. Messai, M. Devignes, A. Napoli, and M. Smal-tabbone, Querying a Bioinformatic Data Sources Registry with Concept Lattices, Proceedings of ICCS 2005, pp.323-336, 2005.
DOI : 10.1007/11524564_22

URL : https://hal.archives-ouvertes.fr/inria-00000102

A. Napoli, A SMOOTH INTRODUCTION TO SYMBOLIC METHODS FOR KNOWLEDGE DISCOVERY, Handbook of Categorization in Cognitive Science, pp.913-933, 2005.
DOI : 10.1016/B978-008044612-7/50096-2

URL : https://hal.archives-ouvertes.fr/inria-00001210

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

M. Kai-petersen, L. K. Hansen, and A. Butkus, Computer music modeling and retrieval. genesis of meaning in sound and music. chapter Semantic Contours in Tracks Based on Emotional Tags, pp.45-66, 2009.

U. Priss, Lattice-based information retrieval Knowledge Organization, pp.132-142, 2000.

P. Refaeilzadeh, L. Tang, and H. Liu, Cross-Validation, Encyclopedia of Database Systems, pp.532-538, 2009.
DOI : 10.1007/978-1-4899-7993-3_565-2

F. Ren and D. B. Bracewell, Advanced Information Retrieval, Electronic Notes in Theoretical Computer Science, vol.225, issue.0, pp.303-317, 2009.
DOI : 10.1016/j.entcs.2008.12.082

M. Rouane-hacene, A. Napoli, P. Valtchev, Y. Toussaint, and R. Bendaoud, Ontology Learning from Text using Relational Concept Analysis, International Conference on eTechnologies (MCETECH 08), pp.154-163, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00322007

M. Rouane-hacene, M. Huchard, A. Napoli, and P. Valtchev, A proposal for combining formal concept analysis and description logics for mining relational data, Proceedings of ICFCA 2007, pp.51-65, 2007.
URL : https://hal.archives-ouvertes.fr/lirmm-00163364

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

G. Sharma and M. N. Murty, Mining Sentiments from Songs Using Latent Dirichlet Allocation, Proceedings of the 10th international conference on Advances in intelligent data analysis X, IDA'11, pp.328-339, 2011.
DOI : 10.1017/CBO9780511809071

T. Stahl, M. Voelter, and K. Czarnecki, Model-Driven Software Development: Technology, Engineering, Management, 2006.

X. Su and T. M. Khoshgoftaar, A survey of collaborative filtering techniques Advances in Artificial Intelligence, pp.2-4, 2009.

L. Szathmary, P. Valtchev, A. Napoli, and R. Godin, Constructing Iceberg Lattices from Frequent Closures Using Generators, Discovery Science, pp.136-147, 2008.
DOI : 10.1007/978-3-540-88411-8_15

URL : https://hal.archives-ouvertes.fr/inria-00331524

L. Szathmary, P. Valtchev, A. Napoli, and R. Godin, Efficient Vertical Mining of Frequent Closures and Generators, Proceedings of the 8th International Symposium on Intelligent Data Analysis (IDA-2009), pp.393-404, 2009.
DOI : 10.1007/978-3-540-88411-8_15

URL : https://hal.archives-ouvertes.fr/inria-00618805

D. Turnbull, L. Barrington, D. Torres, and G. Lanckriet, Semantic Annotation and Retrieval of Music and Sound Effects, IEEE Transactions on Audio, Speech, and Language Processing, vol.16, issue.2, pp.467-476, 2008.
DOI : 10.1109/TASL.2007.913750

R. Typke, F. Wiering, and R. C. Veltkamp, A survey of music information retrieval systems, Proceedings of the 6th International Conference on Music Information Retrieval, 2005.

A. Wang, The Shazam music recognition service, Communications of the ACM, vol.49, issue.8, pp.44-48, 2006.
DOI : 10.1145/1145287.1145312

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

Z. Wu and M. Palmer, Verbs semantics and lexical selection, Proceedings of the 32nd annual meeting on Association for Computational Linguistics -, pp.133-138, 1994.
DOI : 10.3115/981732.981751

M. J. Zaki, Efficient algorithms for mining closed itemsets and their lattice structure, IEEE Transactions on Knowledge and Data Engineering, vol.17, issue.4, pp.462-478, 2005.
DOI : 10.1109/TKDE.2005.60