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  • The Inria's Research Teams produce an annual Activity Report presenting their activities and their results of the year. These reports include the team members, the scientific program, the software developed by the team and the new results of the year. The report also describes the grants, contracts and the activities of dissemination and teaching. Finally, the report gives the list of publications of the year.

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Bibliography

Major publications by the team in recent years
  • 1M. Alam, A. Buzmakov, A. Napoli.

    Exploratory Knowledge Discovery over Web of Data, in: Discrete Applied Mathematics, 2018, vol. 249, pp. 2-17.

    https://hal.inria.fr/hal-01673439
  • 2M. Ansdell, Y. Ioannou, H. Osborn, M. Sasdelli, J. Smith, D. Caldwell, J. Jenkins, C. Raïssi, D. Angerhausen.

    Scientific Domain Knowledge Improves Exoplanet Transit Classification with Deep Learning, in: The Astrophysical Journal Letters, December 2018, vol. 869, no 1, L7 p. [ DOI : 10.3847/2041-8213/aaf23b ]

    https://hal.inria.fr/hal-01957950
  • 3M. Couceiro, M. Maróti, T. Waldhauser, L. Zadori.

    Computing version spaces in the qualitative approach to multicriteria decision aid , in: International Journal of Foundations of Computer Science, 2018.

    https://hal.inria.fr/hal-01404590
  • 4A. Coulet, N. H. Shah, M. Wack, M. Chawki, N. Jay, M. Dumontier.

    Predicting the need for a reduced drug dose, at first prescription, in: Scientific Reports, October 2018, vol. 8, no 1. [ DOI : 10.1038/s41598-018-33980-0 ]

    https://hal.inria.fr/hal-01901566
  • 5J.-F. Mari, A. Gobillot, M. Benoît.

    Time Space Simulation of Land Use changes by stochastic modeling, in: Revue Internationale de Géomatique, August 2018, vol. 28, no 2, pp. 219 - 242.

    https://hal.inria.fr/hal-01662140
Publications of the year

Articles in International Peer-Reviewed Journals

  • 6M. Alam, A. Buzmakov, A. Napoli.

    Exploratory Knowledge Discovery over Web of Data, in: Discrete Applied Mathematics, 2018, vol. 249, pp. 2-17. [ DOI : 10.1016/j.dam.2018.03.041 ]

    https://hal.inria.fr/hal-01673439
  • 7M. Ansdell, Y. Ioannou, H. Osborn, M. Sasdelli, J. Smith, D. Caldwell, J. Jenkins, C. Raïssi, D. Angerhausen.

    Scientific Domain Knowledge Improves Exoplanet Transit Classification with Deep Learning, in: The Astrophysical journal letters, December 2018, vol. 869, no 1, L7 p. [ DOI : 10.3847/2041-8213/aaf23b ]

    https://hal.inria.fr/hal-01957950
  • 8J. Baixeries, V. Codocedo, M. Kaytoue, A. Napoli.

    Characterizing Approximate-Matching Dependencies in Formal Concept Analysis with Pattern Structures, in: Discrete Applied Mathematics, 2018, vol. 249, pp. 18-27. [ DOI : 10.1016/j.dam.2018.03.073 ]

    https://hal.inria.fr/hal-01673441
  • 9G. Bosc, J.-F. Boulicaut, C. Raïssi, M. Kaytoue.

    Anytime Discovery of a Diverse Set of Patterns with Monte Carlo Tree Search, in: Data Mining and Knowledge Discovery, 2018, vol. 32, no 3, pp. 604-650. [ DOI : 10.1007/s10618-017-0547-5 ]

    https://hal.archives-ouvertes.fr/hal-01662857
  • 10Q. Brabant, M. Couceiro.

    k-maxitive Sugeno integrals as aggregation models for ordinal preferences, in: Fuzzy Sets and Systems, 2018, vol. 343, pp. 65-75. [ DOI : 10.1016/j.fss.2017.06.005 ]

    https://hal.archives-ouvertes.fr/hal-01657107
  • 11Q. Brabant, M. Couceiro, J. R. Figueira.

    Interpolation by lattice polynomial functions: a polynomial time algorithm, in: Fuzzy Sets and Systems, 2018. [ DOI : 10.1016/j.fss.2018.12.009 ]

    https://hal.archives-ouvertes.fr/hal-01958903
  • 12M. Couceiro, J. Devillet, J.-L. Marichal.

    Characterizations of idempotent discrete uninorms, in: Fuzzy Sets and Systems, 2018, vol. 334, no 60-72, https://arxiv.org/abs/1701.07253v1. [ DOI : 10.1016/j.fss.2017.06.013 ]

    https://hal.inria.fr/hal-01447513
  • 13M. Couceiro, J. Devillet, J.-L. Marichal.

    Quasitrivial semigroups: Characterizations and enumerations, in: Semigroup Forum, 2018, 22 p. [ DOI : 10.1007/s00233-018-9928-3 ]

    https://hal.inria.fr/hal-01826868
  • 14M. Couceiro, L. Haddad, K. Schölzel.

    On the lower part of the lattice of partial clones, in: Journal of Multiple-Valued Logic and Soft Computing, 2018.

    https://hal.inria.fr/hal-01826870
  • 15M. Couceiro, E. Lehtonen.

    Majors of functions, in: Order, 2018, vol. 35, no 2, pp. 233-246.

    https://hal.inria.fr/hal-01519377
  • 16M. Couceiro, M. Maróti, T. Waldhauser, L. Zadori.

    Computing version spaces in the qualitative approach to multicriteria decision aid , in: International Journal of Foundations of Computer Science, 2018.

    https://hal.inria.fr/hal-01404590
  • 17M. Couceiro, B. Teheux.

    Pivotal decomposition schemes inducing clones of operations, in: Beiträge zur Algebra und Geometrie / Contributions to Algebra and Geometry, 2018, vol. 59, no 1, pp. 25-40.

    https://hal.inria.fr/hal-01450835
  • 18A. Coulet, N. H. Shah, M. Wack, M. Chawki, N. Jay, M. Dumontier.

    Predicting the need for a reduced drug dose, at first prescription, in: Scientific Reports, October 2018, vol. 8, no 1. [ DOI : 10.1038/s41598-018-33980-0 ]

    https://hal.inria.fr/hal-01901566
  • 19E. Galbrun, P. Miettinen.

    Mining redescriptions with Siren, in: ACM Transactions on Knowledge Discovery from Data (TKDD), 2018, vol. 12, no 1, pp. 6:1–6:30. [ DOI : 10.1145/3007212 ]

    https://hal.archives-ouvertes.fr/hal-01399213
  • 20E. Galbrun, H. Tang, M. Fortelius, I. Žliobaitė.

    Computational biomes: The ecometrics of large mammal teeth, in: Palaeontologia Electronica, 2018, vol. 21, no 21.1.3A, pp. 1-31. [ DOI : 10.26879/786 ]

    https://hal.archives-ouvertes.fr/hal-01726076
  • 21J. Kalofolias, E. Galbrun, P. Miettinen.

    From sets of good redescriptions to good sets of redescriptions, in: Knowledge and Information Systems (KAIS), 2018, pp. 1-34. [ DOI : 10.1007/s10115-017-1149-7 ]

    https://hal.archives-ouvertes.fr/hal-01726071
  • 22J.-F. Mari, A. Gobillot, M. Benoît.

    Time Space Simulation of Land Use changes by stochastic modeling, in: Revue Internationale de Géomatique, August 2018, vol. 28, no 2, pp. 219 - 242.

    https://hal.inria.fr/hal-01662140

International Conferences with Proceedings

  • 23L. Amarù, E. Testa, M. Couceiro, O. Zografos, G. De Micheli, M. Soeken.

    Majority logic synthesis, in: ICCAD 2018 - IEEE/ACM International Conference on Computer-Aided Design, San Diego, United States, November 2018. [ DOI : 10.1145/3240765.3267501 ]

    https://hal.inria.fr/hal-01925946
  • 24Q. Brabant, M. Couceiro, D. Dubois, H. Prade, A. Rico.

    Extracting Decision Rules from Qualitative Data via Sugeno Utility Functionals, in: International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2018), Cadiz, France, Communications in Computer and Information Science book series (CCIS), Springer, Cham, June 2018, vol. 853, pp. 253-265.

    https://hal.inria.fr/hal-01670924
  • 25V. Codocedo, J. Baixeries, M. Kaytoue, A. Napoli.

    Characterizing Covers of Functional Dependencies using FCA, in: CLA 2018 - The 14th International Conference on Concept Lattices and Their Applications, Olomouc, Czech Republic, D. I. Ignatov, L. Nourine (editors), CEUR-WS, June 2018, pp. 279-290.

    https://hal.archives-ouvertes.fr/hal-01856516
  • 26B. Conan-Guez, A. Gély, L. Boudjeloud, A. Blansché.

    K-spectral centroid: extension and optimizations, in: ESANN 2018 - 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges, Belgium, April 2018, pp. 603-608.

    https://hal.archives-ouvertes.fr/hal-01901251
  • 27K. Dalleau, M. Couceiro, M. Smaïl-Tabbone.

    Unsupervised extremely randomized trees, in: PAKDD 2018 - The 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining, Melbourne, Australia, May 2018.

    https://hal.inria.fr/hal-01667317
  • 28M.-D. Devignes, Y. Fransot, Y. Lepage, J. Lieber, E. Nauer, M. Smaïl-Tabbone.

    First steps toward finding relevant pathology-gene pairs using analogy, in: EvoCBR 2018 : Workshop on Evolutionary Computation and CBR at the International Conference on Case-Based Reasoning (ICCBR 2018), Stockholm, Sweden, July 2018.

    https://hal.inria.fr/hal-01906547
  • 29T. Gillard, J. Lieber, E. Nauer.

    Improving Adaptation Knowledge Discovery by Exploiting Negative Cases: First Experiment in a Boolean Setting, in: ICCBR 2018 - 26th International Conference on Case-Based Reasoning, Stockholm, Sweden, July 2018.

    https://hal.inria.fr/hal-01905077
  • 30A. Gély, M. Couceiro, A. Napoli.

    Steps Towards Achieving Distributivity in Formal Concept Analysis, in: CLA 2018 - The 14th International Conference on Concept Lattices and Their Applications, Olomouc, Czech Republic, June 2018, 291 p.

    https://hal.inria.fr/hal-01889163
  • 31N. Juniarta, V. Codocedo, M. Couceiro, A. Napoli.

    Biclustering Based on FCA and Partition Pattern Structures for Recommendation Systems, in: FCA4AI@IJCAI2018 - 6th International Workshop "What can FCA do for Artificial Intelligence?", Stockholm, Sweden, July 2018.

    https://hal.inria.fr/hal-01858409
  • 32N. Juniarta, M. Couceiro, A. Napoli, C. Raïssi.

    Sequence Mining within Formal Concept Analysis for Analyzing Visitor Trajectories, in: SMAP 2018 - 13th International Workshop on Semantic and Social Media Adaptation and Personalization, Zaragoza, Spain, September 2018.

    https://hal.inria.fr/hal-01887927
  • 33N. Juniarta, M. Couceiro, A. Napoli, C. Raïssi.

    Sequential Pattern Mining using FCA and Pattern Structures for Analyzing Visitor Trajectories in a Museum, in: CLA 2018 - The 14th International Conference on Concept Lattices and Their Applications, Olomouc, Czech Republic, June 2018.

    https://hal.inria.fr/hal-01887914
  • 34J. Legrand, Y. Toussaint, C. Raïssi, A. Coulet.

    Syntax-based Transfer Learning for the Task of Biomedical Relation Extraction, in: LOUHI 2018 - The Ninth International Workshop on Health Text Mining and Information Analysis, Brussels, Belgium, Proceedings of LOUHI 2018: The Ninth International Workshop on Health Text Mining and Information Analysis, October 2018.

    https://hal.inria.fr/hal-01869071
  • 35Y. Lepage, J. Lieber.

    Case-Based Translation: First Steps from a Knowledge-Light Approach Based on Analogy to a Knowledge-Intensive One, in: ICCBR 2018 - 26th International Conference on Case-Based Reasoning, Stockholm, Sweden, July 2018.

    https://hal.inria.fr/hal-01906528
  • 36J. Lieber, E. Nauer, H. Prade, G. Richard.

    Making the Best of Cases by Approximation, Interpolation and Extrapolation, in: ICCBR 2018 - 26th International Conference on Case-Based Reasoning, Stockholm, Sweden, July 2018.

    https://hal.inria.fr/hal-01905058
  • 37T. Makhalova, S. O. Kuznetsov, A. Napoli.

    A First Study on What MDL Can Do for FCA, in: CLA 2018 - The 14th International Conference on Concept Lattices and Their Applications, Olomouc, Czech Republic, D. I. Ignatov, L. Nourine (editors), June 2018.

    https://hal.archives-ouvertes.fr/hal-01888453
  • 38T. Makhalova, S. O. Kuznetsov, A. Napoli.

    How to improve itemset assessment using minimum description length principle, in: RCAI-2018 - Russian Conference on Artificial Intelligence, Moscou, Russia, September 2018.

    https://hal.archives-ouvertes.fr/hal-01889791
  • 39T. Makhalova, S. O. Kuznetsov, A. Napoli.

    MDL for FCA: is there a place for background knowledge?, in: IJCAI ECAI 2018 - 6th International Workshop "What can FCA do for Artificial Intelligence?", Stockholm, Sweden, July 2018.

    https://hal.archives-ouvertes.fr/hal-01888440
  • 40P. Monnin.

    Discovering and Comparing Relational Knowledge, the Example of Pharmacogenomics, in: EKAW 2018 - 21st International Conference on Knowledge Engineering and Knowledge Management, Nancy, France, November 2018.

    https://hal.inria.fr/hal-01955424
  • 41P. Monnin, A. Napoli, A. Coulet.

    Combining Concept Annotation and Pattern Structures for Guiding Ontology Mapping, in: FCA4AI@IJCAI2018 - 6th International Workshop "What can FCA do for Artificial Intelligence?", Stockholm, Sweden, S. O. Kuznetsov, A. Napoli, S. Rudolph (editors), Proceedings of the 6th International Workshop "What can FCA do for Artificial Intelligence"? co-located with International Joint Conference on Artificial Intelligence and European Conference on Artificial Intelligence (IJCAI/ECAI 2018), Stockholm, Sweden, July 13, 2018, July 2018, vol. CEUR Workshop Proceedings, no 2149.

    https://hal.inria.fr/hal-01858391
  • 42F. Pennerath.

    An Efficient Algorithm for Computing Entropic Measures of Feature Subsets, in: ECML-PKDD 2018 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Dublin, Ireland, September 2018.

    https://hal-centralesupelec.archives-ouvertes.fr/hal-01897734
  • 43G. Personeni, M.-D. Devignes, M. Smaïl-Tabbone, P. Jonveaux, C. Bonnet, A. Coulet.

    Cooperation of bio-ontologies for the classification of genetic intellectual disabilities : a diseasome approach, in: Proceedings of the 11th International Conference on Semantic Web Applications and Tools for Healthcare and Life Sciences (SWAT4HCLS 2018), Antwerp, Belgium, December 2018.

    https://hal.inria.fr/hal-01925471
  • 44J. Reynaud, Y. Toussaint, A. Napoli.

    Three Approaches for Mining Definitions from Relational Data in the Web of Data, in: FCA4AI@IJCAI2018 - 6th International Workshop "What can FCA do for Artificial Intelligence"?, Stockholm, Sweden, July 2018.

    https://hal.inria.fr/hal-01887838

National Conferences with Proceedings

  • 45A. Gély, M. Couceiro, Y. Namir, A. Napoli.

    Contribution à l'étude de la distributivité d'un treillis de concepts, in: EGC 2018 - Extraction et Gestion des Connaissances, Paris, France, Extraction et Gestion des Connaissances, Editions RNTI, January 2018, vol. RNTI-E-34, 478 p.

    https://hal.inria.fr/hal-01889149
  • 46N. Juniarta, V. Codocedo, M. Couceiro, A. Napoli.

    Biclustering Based on FCA and Partition Pattern Structures for Recommendation Systems, in: SFC 2018 - XXVèmes Rencontres de la Société Francophone de Classification, Paris, France, September 2018.

    https://hal.inria.fr/hal-01889309
  • 47J. Lieber, E. Nauer, H. Prade, G. Richard.

    Tirer parti au mieux des cas sources en raisonnement à partir de cas : approximation, interpolation et extrapolation, in: JIAF 2018 - 12èmes Journées d'Intelligence Artificielle Fondamentale, Amiens, France, June 2018, pp. 1-9.

    https://hal.inria.fr/hal-01906519
  • 48J. Reynaud, E. Galbrun, M. Alam, Y. Toussaint, A. Napoli.

    Définir les catégories de DBpedia avec des règles d'associations et des redescriptions, in: EGC 2018 - Extraction et Gestion des Connaissances, Paris, France, January 2018.

    https://hal.inria.fr/hal-01887801
  • 49J. Reynaud, Y. Toussaint, A. Napoli.

    Trois approches pour classifier les données du web des données, in: CNIA/RJCIA 2018 - Conférence Nationale d'Intelligence Artificielle et Rencontres des Jeunes Chercheurs en Intelligence Artificielle, Nancy, France, July 2018.

    https://hal.inria.fr/hal-01887820
  • 50J. Reynaud, Y. Toussaint, A. Napoli.

    Trois approches pour classifier les données du web des données, in: SFC 2018 - XXVèmes Rencontres de la Société Francophone de Classification, Paris, France, September 2018.

    https://hal.inria.fr/hal-01887884

Conferences without Proceedings

  • 51Q. Brabant, M. Couceiro, D. Dubois, H. Prade, A. Rico.

    Sugeno Integral for Rule-Based Ordinal Classification, in: IJCAI-ECAI 2018 - Workshop on Learning and Reasoning: Principles and Applications to Everyday Spatial and Temporal Knowledge, Stockholm, Sweden, July 2018.

    https://hal.archives-ouvertes.fr/hal-01889785
  • 52N. Juniarta, V. Codocedo, M. Couceiro, A. Napoli.

    Biclustering Based on FCA and Partition Pattern Structures for Recommendation Systems, in: NFMCP 2018 - 7th International Workshop on New Frontiers in Mining Complex Patterns, Dublin, Ireland, September 2018.

    https://hal.inria.fr/hal-01889384
  • 53G. Personeni, E. Bresso, M.-D. Devignes, M. Dumontier, M. Smaïl-Tabbone, A. Coulet.

    Découverte d'associations entre Evénements Indésirables Médicamenteux par les structures de patrons et les ontologies, in: Journée I.A. et Santé, Nancy, France, July 2018.

    https://hal.inria.fr/hal-01872312
  • 54M. Schnell, S. Couffignal, J. Lieber, S. Saleh, N. Jay.

    Interpretation of Best Medical Coding Practices by Case-Based Reasoning - A User Assistance Prototype for Data Collection for Cancer Registries, in: JWAIH 2018 - Joint Workshop on Artificial Intelligence in Health, Stockholm, Sweden, July 2018.

    https://hal.archives-ouvertes.fr/hal-01907093
  • 55M. Schnell, S. Couffignal, J. Lieber, S. Saleh, N. Jay.

    Interprétation de bonnes pratiques de codification médicale par du raisonnement à partir de cas - Application à la saisie de données pour les registres du cancer, in: Journée I.A. et Santé, Nancy, France, July 2018.

    https://hal.archives-ouvertes.fr/hal-01907088

Scientific Books (or Scientific Book chapters)

  • 56M. Couceiro, D. Dubois, H. Fargier, M. Grabisch, H. Prade, A. Rico.

    New directions in ordinal evaluation: Sugeno integrals and beyond, in: New Perspectives in Multiple Criteria Decision Making, M. Doumpos, J. Figueira, S. Greco, C. Zopounidis (editors), Springer, 2018.

    https://hal.inria.fr/hal-01941776

Books or Proceedings Editing

  • 57C. Faron Zucker, C. Ghidini, A. Napoli, Y. Toussaint (editors)

    Knowledge Engineering and Knowledge Management, Lecture Notes in Computer Science, Springer, Nancy, France, 2018, vol. 11313. [ DOI : 10.1007/978-3-030-03667-6 ]

    https://hal.inria.fr/hal-01948604
  • 58S. O. Kuznetsov, A. Napoli, S. Rudolph (editors)

    Workshop Notes of the Sixth International Workshop "What can FCA do for Artificial Intelligence?", CEUR Proceedings, Stockholm, Sweden, 2018, vol. 2149, 150 p.

    https://hal.inria.fr/hal-01956367
  • 59W. M. van der Aalst, D. I. Ignatov, A. V. Savchenko, S. Wasserman, M. Khachay, S. O. Kuznetsov, V. Lempitsky, I. A. Lomazova, N. Loukachevitch, A. Napoli, A. Panchenko, P. M. Pardalos (editors)

    Analysis of Images, Social Networks and Texts, Lecture Notes in Computer Science, Springer, Moscow, Russia, 2018, vol. 10716, 412 p. [ DOI : 10.1007/978-3-319-73013-4 ]

    https://hal.inria.fr/hal-01962199

Scientific Popularization

Other Publications

  • 61Q. Brabant, M. Couceiro.

    Sugeno Utility Functionals for Monotonic Classication & Decision Rules, July 2018, ISWS 2018 - International Semantic Web Research Summer School, Poster.

    https://hal.archives-ouvertes.fr/hal-01906052
  • 62M. Couceiro, P. Mercuriali, R. Péchoux, A. Saffidine.

    On the complexity of minimizing median normal forms of monotone Boolean functions and lattice polynomials, 2018, working paper or preprint.

    https://hal.inria.fr/hal-01905491
  • 63N. Juniarta, M. Couceiro, A. Napoli, C. Raïssi.

    Application of Biclustering to the Discovery of Constant and Gradual Patterns, November 2018, APIL 2018 - Annual PhD students conference IAEM Lorraine, Poster.

    https://hal.inria.fr/hal-01935849
  • 64N. Juniarta, M. Couceiro, A. Napoli, C. Raïssi.

    Sequential pattern mining for analyzing visitor trajectories, July 2018, ISWS 2018 - International Semantic Web Research Summer School 2018, Poster.

    https://hal.inria.fr/hal-01890429
  • 65T. Makhalova, S. O. Kuznetsov, A. Napoli.

    What MDL can bring to Pattern Mining, July 2018, ISWS 2018 - International Semantic Web Research Summer School, Poster.

    https://hal.archives-ouvertes.fr/hal-01889792
  • 66P. Monnin, A. Napoli, A. Coulet.

    Data-Interlinking: the Seed of Knowledge Reconciliation in Pharmacogenomics, 2018, working paper or preprint.

    https://hal.inria.fr/hal-01955262
References in notes
  • 67C. C. Aggarwal, C. Zhai (editors)

    Mining Text Data, Springer, 2012.
  • 68F. Baader, D. Calvanese, D. McGuinness, D. Nardi, P. Patel-Schneider (editors)

    The Description Logic Handbook, Cambridge University Press, Cambridge, UK, 2003.
  • 69M. Alam, A. Buzmakov, V. Codocedo, A. Napoli.

    Mining Definitions from RDF Annotations Using Formal Concept Analysis, in: International Joint Conference in Artificial Intelligence, Buenos Aires, Argentina, Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, July 2015.

    https://hal.archives-ouvertes.fr/hal-01186204
  • 70M. Alam, T. N. N. Le, A. Napoli.

    LatViz: A New Practical Tool for Performing Interactive Exploration over Concept Lattices, in: CLA 2016 - Thirteenth International Conference on Concept Lattices and Their Applications, Moscow, Russia, July 2016.

    https://hal.inria.fr/hal-01420751
  • 71M. Barbut, B. Monjardet.

    Ordre et classification – Algèbre et combinatoire (2 tomes), Hachette, Paris, 1970.
  • 72S. Da Silva, F. Le Ber, C. Lavigne.

    Structures de haies dans un paysage agricole : une étude par chemin de Hilbert adaptatif et chaînes de Markov , in: EGC 2016 – 16èemes Journées Francophones ”Extraction et Gestion des Connaissances”, Reims, France, Revue des Nouvelles Technologies de l'Information, January 2016, vol. RNTI-E-30, pp. 279–290.

    https://hal.archives-ouvertes.fr/hal-01266344
  • 73B. Ganter, S. O. Kuznetsov.

    Pattern Structures and Their Projections, in: Proceedings of ICCS 2001, LNCS 2120, Springer, 2001, pp. 129–142.
  • 74B. Ganter, R. Wille.

    Formal Concept Analysis, Springer, Berlin, 1999.
  • 75P. Geurts, D. Ernst, L. Wehenkel.

    Extremely Randomized Trees, in: Machine Learning, 2006, vol. 63, no 1, pp. 3–42.
  • 76M. Grabisch, J.-L. Marichal, R. Mesiar, E. Pap.

    Aggregation Functions, Encyclopedia of Mathematics and its Applications, Cambridge University Press, 2009.
  • 77D. Grissa, B. Comte, E. Pujos-Guillot, A. Napoli.

    A Hybrid Knowledge Discovery Approach for Mining Predictive Biomarkers in Metabolomic Data, in: ECML PKDD, Riva del garda, Italy, September 2016, pp. 572 - 587. [ DOI : 10.1007/978-3-319-46128-1_36 ]

    https://hal.archives-ouvertes.fr/hal-01421011
  • 78O. Hudry, B. Monjardet.

    Consensus Theories. An oriented survey, in: Mathématiques et Sciences Humaines, 2010, vol. 190, no 2, pp. 139–167.
  • 79M. Kaytoue, V. Codocedo, A. Buzmakov, J. Baixeries, S. O. Kuznetsov, A. Napoli.

    Pattern Structures and Concept Lattices for Data Mining and Knowledge Processing, in: Machine Learning and Knowledge Discovery in Databases, Porto, Portugal, A. Bifet, M. May, B. Zadrozny, R. Gavalda, D. Pedreschi, F. Bonchi, J. Cardoso, M. Spiliopoulou (editors), Lecture Notes in Computer Science, Springer International Publishing, 2015, vol. 9286, pp. 227-231. [ DOI : 10.1007/978-3-319-23461-8_19 ]

    https://hal.archives-ouvertes.fr/hal-01188637
  • 80J.-F. Mari, F. Le Ber, E.-G. Lazrak, M. Benoît, C. Eng, A. Thibessard, P. Leblond.

    Using Markov Models to Mine Temporal and Spatial Data, in: New Fundamental Technologies in Data Mining, K. Funatsu, K. Hasegawa (editors), Intech, 2011, pp. 561–584.

    http://hal.inria.fr/inria-00566801/en
  • 81J.-P. Metivier, A. Lepailleur, A. Buzmakov, G. Poezevara, B. Crémilleux, S. O. Kuznetsov, J. Le Goff, A. Napoli, R. Bureau, B. Cuissart.

    Discovering structural alerts for mutagenicity using stable emerging molecular patterns, in: Journal of Chemical Information and Modeling, 2015, vol. 55, no 5, pp. 925–940. [ DOI : 10.1021/ci500611v ]

    https://hal.archives-ouvertes.fr/hal-01186716
  • 82N. Ramakrishnan, D. Kumar, B. Mishra, M. Potts, R. F. Helm.

    Turning CARTwheels: An Alternating Algorithm for Mining Redescriptions, in: Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, NY, USA, KDD '04, ACM, 2004, pp. 266–275.
  • 83J. Reynaud, M. Alam, Y. Toussaint, A. Napoli.

    A Proposal for Classifying the Content of the Web of Data Based on FCA and Pattern Structures, in: International Symposium on Methodologies for Intelligent Systems, Warsaw, Poland, June 2017.

    https://hal.inria.fr/hal-01667437
  • 84M. Rouane-Hacene, M. Huchard, A. Napoli, P. Valtchev.

    Relational Concept Analysis: Mining Concept Lattices From Multi-Relational Data, in: Annals of Mathematics and Artificial Intelligence, January 2013, vol. 67, no 1, pp. 81-108. [ DOI : 10.1007/s10472-012-9329-3 ]

    http://hal.inria.fr/lirmm-00816300
  • 85T. Shi, S. Horvath.

    Unsupervised Learning With Random Forest Predictors, in: Journal of Computational and Graphical Statistics, 2006, vol. 15, no 1, pp. 118-138.
  • 86L. Szathmary, P. Valtchev, A. Napoli, R. Godin, A. Boc, V. Makarenkov.

    A fast compound algorithm for mining generators, closed itemsets, and computing links between equivalence classes, in: Annals of Mathematics and Artificial Intelligence, 2014, vol. 70, pp. 81 - 105. [ DOI : 10.1007/s10472-013-9372-8 ]

    https://hal.inria.fr/hal-01101140