ZENITH: Gestion de données scientifiques

Zenith s’attaque aux défis posés par la gestion (stockage, partage, traitement, recherche analyse) des données massives (big data, données scientifiques). Ces défis (correspondant aux trois big V : Volume, Velocity, Variety) peuvent se résumer ainsi:

1. très grande échelle (big data, big analytics) ;

2. données en continu (produits par des capteurs, des appareils mobiles, …) ;

3. hétérogénéité et complexité des données (différences sémantiques, données incertaines ou multi-échelles, …).

Notre objectif est d’apporter des solutions innovantes, en démontrant des avantages en termes de passage à l’échelle, fonctionnalité, facilité d’usage et performance, dans des environnements distribués et parallèles (P2P, grid, cloud).

Nous cherchons à produire des résultats fondamentaux et algorithmiques, que nous pouvons implémenter dans des environnements spécifiques, par ex. Grid5K. Pour valider nos solutions, nous collaborons avec des partenaires scientifiques (INRA, CIRAD, IRD, etc.) et industriels (Data Publica, Bull, EDF, Orange, Microsoft, MonetDB, Sparsity, etc.).

Membres

Permanents

Non permanents

Collaborateurs réguliers

  • Hervé Goëau
  • Michel Riveill
  • Christophe Pradal

Thématiques de recherche

Le projet Zenith est organisé en trois thèmes complémentaires :

1. Gestion de données et métadonnées : gestion et intégration de données et métadonnées (schémas, ontologies) à grande échelle, en particulier, stockage de big data, résolution d’entités incertaines et traitement de requêtes probabilistes.

2. Partage de données et processus : gestion des données et processus scientifiques dans des environnements distribués et parallèles, avec partage de données en P2P, recommandation dans les communautés en ligne et support des workflows scientifiques.

3. Analyse de données : fouille de données et recherche de données par contenu en exploitant le parallélisme du cloud et les nouvelles technologies NoSQL et MapReduce.

Ces trois thèmes reflètent le continuum qui va de la capture des données, en passant par leur intégration, gestion et partage, jusqu’à leur analyse, afin de produire informations et connaissances.

Publications majeures depuis 2008

R. Akbarinia, P. Valduriez, G. Verger, Efficient Evaluation of SUM Queries Over Probabilistic Data. IEEE Transactions on Knowledge and Data Engineering, Data. Vol. 25, No. 4, 764-775, 2013.

M. El Dick, E. Pacitti, R. Akbarinia, B. Kemme, Building a Peer-to-Peer Content Distribution Network with High Performance, Scalability and Robustness, Information Systems, Vol. 36, No 2, p. 222-247, 2011.

P. Letessier, O. Buisson, A. Joly, N. Boujemaa, Scalable Mining of Small Visual Objects, ACM Multimedia Conf.,  2012.

E. Ogasawara, D. De Oliveira, P. Valduriez, J. Dias, F. Porto, M. Mattoso, An Algebraic Approach for Data-Centric Scientific Workflows, Proceedings of VLDB, Vol. 4, No 11, p. 1328-1339, 2011. 

F. Petitjean, F. Masseglia, P. Gançarski, G. Forestier, Discovering Significant Evolution Patterns from Satelllite Image Time Series, International Journal of Neural Systems, Vol. 21, No 6, 475-489, 2011.

Publications depuis 2014 - Evaluation 2019

Articles de revues internationales

2019

  1. Keeping Track of User Steering Actions in Dynamic Workflows
    Renan Souza, Vítor Silva, José Camata, Alvaro Coutinho, Patrick Valduriez, Marta Mattoso
    Future Generation Computer Systems, Elsevier, 2019, 99, pp.624-643. ⟨10.1016/j.future.2019.05.011⟩. ⟨lirmm-02127456⟩.
  2. CountNet: Estimating the Number of Concurrent Speakers Using Supervised Learning
    Fabian-Robert Stöter, Soumitro Chakrabarty, Bernd Edler, Emanuël Habets
    IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2019, 27 (2), pp.268-282. ⟨10.1109/TASLP.2018.2877892⟩. ⟨lirmm-02010805⟩.
  3. Musical Source Separation: An Introduction
    Estefania Cano, Derry Fitzgerald, Antoine Liutkus, Mark Plumbley, Fabian-Robert Stöter
    IEEE Signal Processing Magazine, Institute of Electrical and Electronics Engineers, 2019, 36 (1), pp.31-40. ⟨http://epubs.surrey.ac.uk/id/eprint/849940⟩. ⟨10.1109/MSP.2018.2874719⟩. ⟨hal-01945345⟩.
  4. Parallel Computation of PDFs on Big Spatial Data Using Spark
    Ji Liu, Noel Moreno Lemus, Esther Pacitti, Fábio Porto, Patrick Valduriez
    Distributed and Parallel Databases, Springer, In press, pp.1-38. ⟨10.1007/s10619-019-07260-3⟩. ⟨lirmm-02045144⟩.

2018

  1. ParCorr: efficient parallel methods to identify similar time series pairs across sliding windows
    Djamel-Edine Yagoubi, Reza Akbarinia, Boyan Kolev, Oleksandra Levchenko, Florent Masseglia, Patrick Valduriez, Dennis Shasha
    Data Mining and Knowledge Discovery, Springer, 2018, 32 (5), pp.1481-1507. ⟨10.1007/s10618-018-0580-z⟩. ⟨lirmm-01886794⟩.
  2. Genetic and environmental dissection of biomass accumulation in multi-genotype maize canopies
    Tsu-Wei Chen, Llorenç Cabrera-Bosquet, Santiago Alvarez Prado, Raphael Perez, Simon Artzet, Christophe Pradal, Aude Coupel-Ledru, Christian Fournier, Francois Tardieu
    Journal of Experimental Botany, Oxford University Press (OUP), 2018, &#x27E8;10.1093/jxb/ery309&#x27E9;. &#x27E8;hal-01895279&#x27E9;. <10.1093/jxb/ery309>
  3. DfAnalyzer: Runtime Dataflow Analysis of Scientific Applications using Provenance
    Vítor Silva, Daniel de Oliveira, Patrick Valduriez, Marta Mattoso
    Proceedings of the VLDB Endowment (PVLDB), VLDB Endowment, 2018, 11 (12), pp.2082-2085. &#x27E8;http://www.vldb.org/pvldb/&#x27E9;. &#x27E8;10.14778/3229863.3236265&#x27E9;. &#x27E8;lirmm-01867887&#x27E9;.
  4. Non-parametric Bayesian annotator combination
    Maximilien Servajean, Romain Chailan, Alexis Joly
    Information Sciences, Elsevier, 2018, 436-437, pp.131-145. &#x27E8;10.1016/j.ins.2018.01.020&#x27E9;. &#x27E8;lirmm-01703020&#x27E9;.
  5. Species distribution modeling based on the automated identification of citizen observations
    Christophe Botella, Alexis Joly, Pierre Bonnet, Pascal Monestiez, François Munoz
    Applications in Plant Sciences, Wiley, 2018, Green Digitization: Online Botanical Collections Data Answering Real‐World Questions, 6 (2), pp.1-11. &#x27E8;10.1002/aps3.1029&#x27E9;. &#x27E8;hal-01739481&#x27E9;.
  6. Distributed Management of Scientific Workflows for High-Throughput Plant Phenotyping
    Christophe Pradal, Sarah Cohen-Boulakia, Gaetan Heidsieck, Esther Pacitti, Francois Tardieu, Patrick Valduriez
    ERCIM News, ERCIM, 2018, Smart Farming, pp.36-37. &#x27E8;https://ercim-news.ercim.eu/en113/special/distributed-management-of-scientific-workflows-for-high-throughput-plant-phenotyping&#x27E9;. &#x27E8;hal-01948568&#x27E9;.
  7. In situ visualization and data analysis for turbidity currents simulation
    José Camata, Vitor Silva, Patrick Valduriez, Marta Mattoso, Alvaro Coutinho
    Computers & Geosciences, Elsevier, 2018, 110, pp.23-31. &#x27E8;10.1016/j.cageo.2017.09.013&#x27E9;. &#x27E8;lirmm-01620127&#x27E9;.
  8. Efficient Scheduling of Scientific Workflows using Hot Metadata in a Multisite Cloud
    Ji Liu, Luis Pineda, Esther Pacitti, Alexandru Costan, Patrick Valduriez, Gabriel Antoniu, Marta Mattoso
    IEEE Transactions on Knowledge and Data Engineering, Institute of Electrical and Electronics Engineers, In press, pp.1-20. &#x27E8;10.1109/TKDE.2018.2867857&#x27E9;. &#x27E8;lirmm-01867717&#x27E9;.
  9. AutoWIG: automatic generation of python bindings for C++ libraries
    Pierre Fernique, Christophe Pradal
    PeerJ Computer Science, PeerJ, 2018, 4, &#x27E8;10.7717/peerj-cs.149&#x27E9;. &#x27E8;hal-01756458&#x27E9;. <10.7717/peerj-cs.149>
  10. A Survey of Scheduling Frameworks in Big Data Systems
    Ji Liu, Esther Pacitti, Patrick Valduriez
    International Journal of Cloud Computing, Inderscience Publishers, 2018, 7 (2), pp.103-128. &#x27E8;10.1504/IJCC.2018.093765&#x27E9;. &#x27E8;lirmm-01692229&#x27E9;.
  11. An Overview of Lead and Accompaniment Separation in Music
    Zafar Rafii, Antoine Liutkus, Fabian-Robert Stöter, Stylianos Ioannis Mimilakis, Derry Fitzgerald, Bryan Pardo
    IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2018, 26 (8), pp.1307-1335. &#x27E8;10.1109/TASLP.2018.2825440&#x27E9;. &#x27E8;lirmm-01766781&#x27E9;.
  12. Data reduction in scientific workflows using provenance monitoring and user steering
    Renan Souza, Vitor Silva, Alvaro L.G.A. Coutinho, Patrick Valduriez, Marta Mattoso
    Future Generation Computer Systems, Elsevier, In press, pp.1-21. &#x27E8;10.1016/j.future.2017.11.028&#x27E9;. &#x27E8;lirmm-01679967&#x27E9;.

2017

  1. Going deeper in the automated identification of Herbarium specimens
    Jose Carranza-Rojas, Herve Goeau, Pierre Bonnet, Erick Mata-Montero, Alexis Joly
    BMC Evolutionary Biology, BioMed Central, 2017, 17 (1), pp.181. &#x27E8;10.1186/s12862-017-1014-z&#x27E9;. &#x27E8;hal-01580070&#x27E9;.
  2. Crowdsourcing Thousands of Specialized Labels: A Bayesian Active Training Approach
    Maximilien Servajean, Alexis Joly, Dennis Shasha, Julien Champ, Esther Pacitti
    IEEE Transactions on Multimedia, Institute of Electrical and Electronics Engineers, 2017, 19 (6), pp.1376-1391. &#x27E8;10.1109/TMM.2017.2653763&#x27E9;. &#x27E8;hal-01629149&#x27E9;.
  3. InfraPhenoGrid: A scientific workflow infrastructure for Plant Phenomics on the Grid
    Christophe Pradal, Simon Artzet, Jerome Chopard, Dimitri Dupuis, Christian Fournier, Michael Mielewczik, Vincent Negre, Pascal Neveu, Didier Parigot, Patrick Valduriez, Sarah Cohen-Boulakia
    Future Generation Computer Systems, Elsevier, 2017, 67, pp.341-353. &#x27E8;10.1016/j.future.2016.06.002&#x27E9;. &#x27E8;hal-01336655&#x27E9;.
  4. A Highly Scalable Parallel Algorithm for Maximally Informative k-Itemset Mining
    Saber Salah, Reza Akbarinia, Florent Masseglia
    Knowledge and Information Systems (KAIS), Springer, 2017, 50 (1), pp.1-26. &#x27E8;10.1007/s10115-016-0931-2&#x27E9;. &#x27E8;lirmm-01288571&#x27E9;.
  5. Scientific Workflow Scheduling with Provenance Data in a Multisite Cloud
    Ji Liu, Esther Pacitti, Patrick Valduriez, Marta Mattoso
    Transactions on Large-Scale Data- and Knowledge-Centered Systems, Springer Berlin / Heidelberg, 2017, 33, pp.80-112. &#x27E8;10.1109/IPDPS.2007.370305&#x27E9;. &#x27E8;lirmm-01620224&#x27E9;.
  6. Data placement in massively distributed environments for fast parallel mining of frequent itemsets
    Saber Salah, Reza Akbarinia, Florent Masseglia
    Knowledge and Information Systems (KAIS), Springer, 2017, 53 (1), pp.207-237. &#x27E8;10.1007/s10115-017-1041-5&#x27E9;. &#x27E8;lirmm-01620383&#x27E9;.
  7. Raw data queries during data-intensive parallel workflow execution
    Vítor Silva, José Leite, José Camata, Daniel de Oliveira, Alvaro Coutinho, Patrick Valduriez, Marta Mattoso
    Future Generation Computer Systems, Elsevier, 2017, 75, pp.402-422. &#x27E8;10.1016/j.future.2017.01.016&#x27E9;. &#x27E8;lirmm-01445219&#x27E9;.
  8. Scientific workflows for computational reproducibility in the life sciences: Status, challenges and opportunities
    Sarah Cohen-Boulakia, Khalid Belhajjame, Olivier Collin, Jérôme Chopard, Christine Froidevaux, Alban Gaignard, Konrad Hinsen, Pierre Larmande, Yvan Le Bras, Frédéric Lemoine, Fabien Mareuil, Hervé Ménager, Christophe Pradal, Christophe Blanchet
    Future Generation Computer Systems, Elsevier, 2017, &#x27E8;10.1016/j.future.2017.01.012&#x27E9;. &#x27E8;hal-01516082&#x27E9;. <10.1016/j.future.2017.01.012>

2016

  1. CloudMdsQL: Querying Heterogeneous Cloud Data Stores with a Common Language
    Boyan Kolev, Patrick Valduriez, Carlyna Bondiombouy, Ricardo Jiménez-Peris, Raquel Pau, José Pereira
    Distributed and Parallel Databases, Springer, 2016, 34 (4), pp.463-503. &#x27E8;10.1007/s10619-015-7185-y&#x27E9;. &#x27E8;lirmm-01184016&#x27E9;.
  2. AgroLD API. Une architecture orientée services pour l'extraction de connaissances dans la base de données liées AgroLD
    Gildas Tagny Ngompe, Aravind Venkatesan, Nordine El Hassouni, Manuel Ruiz, Pierre Larmande
    Revue des Sciences et Technologies de l'Information - Série ISI : Ingénierie des Systèmes d'Information, Lavoisier, 2016, 21 (5-6), pp.133-158. &#x27E8;https://isi.revuesonline.com/article.jsp?articleId=37163&#x27E9;. &#x27E8;10.3166/isi.21.5-6.133-157&#x27E9;. &#x27E8;hal-01411532&#x27E9;.
  3. Categorizing plant images at the variety level: Did you say fine-grained?
    Julien Champ, Titouan Lorieul, Pierre Bonnet, Najate Maghnaoui, Christophe Sereno, Thierry Dessup, Jean-Michel Boursiquot, Laurent Audeguin, Thierry Lacombe, Alexis Joly
    Pattern Recognition Letters, Elsevier, 2016, 81, pp.71-79. &#x27E8;10.1016/j.patrec.2016.05.022&#x27E9;. &#x27E8;lirmm-01348914&#x27E9;.
  4. Database System Support of Simulation Data
    Hermano Lustosa, Fabio Porto, Pablo Blanco, Patrick Valduriez
    Proceedings of the VLDB Endowment (PVLDB), VLDB Endowment, 2016, 9 (13), pp.1329-1340. &#x27E8;http://www.vldb.org/pvldb/vol9/p1329-lustosa.pdf&#x27E9;. &#x27E8;lirmm-01363738&#x27E9;.
  5. Gigwa—Genotype investigator for genome- wide analyses
    Guilhem Sempéré, Florian Philippe, Alexis Dereeper, Manuel Ruiz, Gautier Sarah, Pierre Larmande
    GigaScience, BioMed Central, 2016, &#x27E8;10.1186/s13742-016-0131-8&#x27E9;. &#x27E8;hal-01411506&#x27E9;. <10.1186/s13742-016-0131-8>
  6. Social Networks and Information Retrieval, How Are They Converging? A Survey, a Taxonomy and an Analysis of Social Information Retrieval Approaches and Platforms
    Mohamed Reda Bouadjenek, Hakim Hacid, Mokrane Bouzeghoub
    Information Systems, Elsevier, 2016, 56, pp.1-18. &#x27E8;10.1016/j.is.2015.07.008&#x27E9;. &#x27E8;lirmm-01174843v4&#x27E9;.
  7. Analyzing Related Raw Data Files through Dataflows
    Vitor Silva, Daniel De Oliveira, Patrick Valduriez, Marta Mattoso
    Concurrency and Computation: Practice and Experience, Wiley, 2016, 28 (8), pp.2528-2545. &#x27E8;10.1002/cpe.3616&#x27E9;. &#x27E8;lirmm-01181231&#x27E9;.
  8. Guest Editorial: Environmental Multimedia Retrieval
    Stefanos Vrochidis, Kostas D. Karatzas, Ari Karppinen, Alexis Joly
    Multimedia Tools and Applications, Springer Verlag, 2016, 75 (3), pp.1557--1562. &#x27E8;10.1007/s11042-016-3256-y&#x27E9;. &#x27E8;hal-01373782&#x27E9;.
  9. Plant identification: Man vs. Machine
    Pierre Bonnet, Alexis Joly, Hervé Goëau, Julien Champ, Christel Vignau, Jean-François Molino, Daniel Barthélémy, Nozha Boujemaa
    Multimedia Tools and Applications, Springer Verlag, 2016, LifeCLEF 2014 plant identification challenge, 75 (3), pp.1647-1665. &#x27E8;10.1007/s11042-015-2607-4&#x27E9;. &#x27E8;hal-01182778&#x27E9;.
  10. FP-Hadoop: Efficient Processing of Skewed MapReduce Jobs
    Miguel Liroz-Gistau, Reza Akbarinia, Divyakant Agrawal, Patrick Valduriez
    Information Systems, Elsevier, 2016, 60, pp.69-84. &#x27E8;10.1016/j.is.2016.03.008&#x27E9;. &#x27E8;lirmm-01377715&#x27E9;.
  11. Multistore Big Data Integration with CloudMdsQL
    Carlyna Bondiombouy, Boyan Kolev, Oleksandra Levchenko, Patrick Valduriez
    Transactions on Large-Scale Data- and Knowledge-Centered Systems, Springer Berlin / Heidelberg, 2016, 28, pp.48-74. &#x27E8;lirmm-01345712&#x27E9;.
  12. A look inside the Pl@ntNet experience
    Alexis Joly, Pierre Bonnet, Hervé Goëau, Julien Barbe, Souheil Selmi, Julien Champ, Samuel Dufour-Kowalski, Antoine Affouard, Jennifer Carré, Jean-François Molino, Nozha Boujemaa, Daniel Barthélémy
    Multimedia Systems, Springer Verlag, 2016, 22 (6), pp.751-766. &#x27E8;10.1007/s00530-015-0462-9&#x27E9;. &#x27E8;hal-01182775&#x27E9;.
  13. Query processing in multistore systems: an overview
    Carlyna Bondiombouy, Patrick Valduriez
    International Journal of Cloud Computing, Inderscience Publishers, 2016, pp.38. &#x27E8;http://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=IJCC&#x27E9;. &#x27E8;lirmm-01341158&#x27E9;.
  14. Multi-Objective Scheduling of Scientific Workflows in Multisite Clouds
    Ji Liu, Esther Pacitti, Patrick Valduriez, Daniel de Oliveira, Marta Mattoso
    Future Generation Computer Systems, Elsevier, 2016, 63, pp.76-95. &#x27E8;10.1016/j.future.2016.04.014&#x27E9;. &#x27E8;lirmm-01342203&#x27E9;.
  15. Effective and Efficient Similarity Search in Scientific Workflow Repositories
    Johannes Starlinger, Sarah Cohen-Boulakia, Sanjeev Khanna, Susan Davidson, Ulf Leser
    Future Generation Computer Systems, Elsevier, 2016, 56, pp.584-594. &#x27E8;10.1016/j.future.2015.06.012&#x27E9;. &#x27E8;hal-01170597&#x27E9;.

2015

  1. Rank aggregation with ties: Experiments and Analysis
    Bryan Brancotte, Bo Yang, Guillaume Blin, Sarah Cohen-Boulakia, Alain Denise, Sylvie Hamel
    Proceedings of the VLDB Endowment (PVLDB), VLDB Endowment, 2015, pp.2051. &#x27E8;hal-01165336&#x27E9;.
  2. Increasing Coverage in Distributed Search and Recommendation with Profile Diversity
    Maximilien Servajean, Esther Pacitti, Miguel Liroz-Gistau, Sihem Amer-Yahia, Amr El Abbadi
    Transactions on Large-Scale Data- and Knowledge-Centered Systems, Springer Berlin / Heidelberg, 2015, LNCS (9430), pp.115-144. &#x27E8;10.1007/978-3-662-48567-5_4&#x27E9;. &#x27E8;lirmm-01177817&#x27E9;.
  3. Profile Diversity for Query Processing using User Recommendations
    Maximilien Servajean, Reza Akbarinia, Esther Pacitti, Sihem Amer-Yahia
    Information Systems, Elsevier, 2015, Information Systems, 48, pp.44-63. &#x27E8;10.1016/j.is.2014.09.001&#x27E9;. &#x27E8;lirmm-01079523&#x27E9;.
  4. FP-Hadoop: Efficient Execution of Parallel Jobs Over Skewed Data
    Miguel Liroz-Gistau, Reza Akbarinia, Patrick Valduriez
    Proceedings of the VLDB Endowment (PVLDB), VLDB Endowment, 2015, 8 (12), pp.1856-1867. &#x27E8;lirmm-01162362&#x27E9;.
  5. A Survey of Data-Intensive Scientific Workflow Management
    Ji Liu, Esther Pacitti, Patrick Valduriez, Marta Mattoso
    Journal of Grid Computing, Springer Verlag, 2015, 13, 44 p. &#x27E8;10.1007/s10723-015-9329-8&#x27E9;. &#x27E8;lirmm-01144760&#x27E9;. <10.1007/s10723-015-9329-8>
  6. Data-Centric Iteration in Dynamic Workflows
    Jonas Dias, Gabriel Guerra, Fernando Rochinha, Alvaro Coutinho, Patrick Valduriez, Marta Mattoso
    Future Generation Computer Systems, Elsevier, 2015, 46, pp.114-126. &#x27E8;10.1016/j.future.2014.10.021&#x27E9;. &#x27E8;lirmm-01073638&#x27E9;.

2014

  1. Autonomic Intrusion Detection: Adaptively Detecting Anomalies over Unlabeled Audit Data Streams in Computer Networks
    Wei Wang, Thomas Guyet, René Quiniou, Marie-Odile Cordier, Florent Masseglia, Xiangliang Zhang
    Knowledge-Based Systems, Elsevier, 2014. &#x27E8;hal-01052810&#x27E9;.
  2. Special section on data-intensive cloud infrastructure
    Ashraf Aboulnaga, Beng Chin Ooi, Patrick Valduriez
    The VLDB Journal, Springer, 2014, pp.1. &#x27E8;http://link.springer.com/article/10.1007/s00778-014-0371-0&#x27E9;. &#x27E8;10.1007/s00778-014-0371-0&#x27E9;. &#x27E8;lirmm-01073589&#x27E9;.
  3. The anti-bouncing data stream model for web usage streams with intralinkings
    Chongsheng Zhang, Florent Masseglia, Yves Lechevallier
    Information Sciences, Elsevier, 2014, 278, pp.757-772. &#x27E8;http://www.sciencedirect.com/science/article/pii/S0020025514003806&#x27E9;. &#x27E8;10.1016/j.ins.2014.03.089&#x27E9;. &#x27E8;lirmm-01091868&#x27E9;.
  4. Similarity Search for Scientific Workflows
    Johannes Starlinger, Bryan Brancotte, Sarah Cohen-Boulakia, Ulf Leser
    Proceedings of the VLDB Endowment (PVLDB), VLDB Endowment, 2014, 7 (12), pp.1143-1154. &#x27E8;10.14778/2732977.2732988&#x27E9;. &#x27E8;hal-01066046&#x27E9;.
  5. Evaluation of Direct Manipulation using Finger Tracking for Complex Tasks in an Immersive Cube
    Emmanuelle Chapoulie, Maud Marchal, Evanthia Dimara, Maria Roussou, Jean-Christophe Lombardo, George Drettakis
    Virtual Reality, Springer Verlag, 2014, pp.15. &#x27E8;hal-01060303&#x27E9;.
  6. Query Reformulation in PDMS Based on Social Relevance
    Angela Bonifati, Gianvito Summa, Esther Pacitti, Fady Draidi
    Transactions on Large-Scale Data- and Knowledge-Centered Systems, Springer Berlin / Heidelberg, 2014, Transactions on Large-Scale Data- and Knowledge-Centered Systems XIII, LNCS, pp.59-90. &#x27E8;10.1007/978-3-642-54426-2_3&#x27E9;. &#x27E8;lirmm-01088153&#x27E9;.
  7. Object-based visual query suggestion
    Amel Hamzaoui, Pierre Letessier, Alexis Joly, Olivier Buisson, Nozha Boujemaa
    Multimedia Tools and Applications, Springer Verlag, 2014, Multimedia Tools and Applications, 68 (2), pp.429-454. &#x27E8;10.1007/s11042-012-1340-5&#x27E9;. &#x27E8;hal-00806635&#x27E9;.
  8. Dynamic Workload-Based Partitioning Algorithms for Continuously Growing Databases
    Miguel Liroz-Gistau, Reza Akbarinia, Esther Pacitti, Fabio Porto, Patrick Valduriez
    Transactions on Large-Scale Data- and Knowledge-Centered Systems, Springer Berlin / Heidelberg, 2014, pp.105. &#x27E8;lirmm-00906966&#x27E9;.
  9. Entity Resolution for Probabilistic Data
    Ayat Naser, Reza Akbarinia, Hamideh Afsarmanesh, Patrick Valduriez
    Information Sciences, Elsevier, 2014, 277, pp.492-511. &#x27E8;10.1016/j.ins.2014.02.135&#x27E9;. &#x27E8;lirmm-01076096&#x27E9;.
  10. Interactive plant identification based on social image data
    Alexis Joly, Hervé Goëau, Pierre Bonnet, Vera Bakić, Julien Barbe, Souheil Selmi, Itheri Yahiaoui, Jennifer Carré, Elise Mouysset, Jean-François Molino, Nozha Boujemaa, Daniel Barthélémy
    Ecological Informatics, Elsevier, 2014, 23, pp.22-34. &#x27E8;10.1016/j.ecoinf.2013.07.006&#x27E9;. &#x27E8;hal-00908872v2&#x27E9;.

Communications internationales

2019

  1. Speech enhancement with variational autoencoders and alpha-stable distributions
    Simon Leglaive, Umut Simsekli, Antoine Liutkus, Laurent Girin, Radu Horaud
    ICASSP 2019 - IEEE International Conference on Acoustics Speech and Signal Processing, May 2019, Brighton, United Kingdom. pp.541-545, &#x27E8;10.1109/ICASSP.2019.8682546&#x27E9;. &#x27E8;hal-02005106&#x27E9;.
  2. Dirichlet Process Mixture Models made Scalable and Effective by means of Massive Distribution
    Khadidja Meguelati, Bénédicte Fontez, Nadine Hilgert, Florent Masseglia
    SAC: Symposium on Applied Computing, Apr 2019, Limassol, Cyprus. &#x27E8;10.1145/3297280.3297327&#x27E9;. &#x27E8;hal-01999453&#x27E9;. <10.1145/3297280.3297327>

2018

  1. Parallel Polyglot Query Processing on Heterogeneous Cloud Data Stores with LeanXcale
    Boyan Kolev, Oleksandra Levchenko, Esther Pacitti, Patrick Valduriez, Ricardo Vilaça, Rui Gonçalves, Ricardo Jiménez-Peris, Pavlos Kranas
    IEEE BigData, Dec 2018, Seattle, United States. pp.10. &#x27E8;lirmm-01921718&#x27E9;.
  2. Spark-parSketch: A Massively Distributed Indexing of Time Series Datasets
    Oleksandra Levchenko, Djamel-Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Boyan Kolev, Dennis Shasha
    CIKM: Conference on Information and Knowledge Management, Oct 2018, Turin, Italy. pp.1951-1954, &#x27E8;10.1145/3269206.3269226&#x27E9;. &#x27E8;lirmm-01886760&#x27E9;.
  3. SiSEC 2018: State of the art in musical audio source separation - subjective selection of the best algorithm
    Dominic Ward, Russel D. Mason, Chungeun Kim, Fabian-Robert Stöter, Antoine Liutkus, Mark Plumbley
    WIMP: Workshop on Intelligent Music Production, Sep 2018, Huddersfield, United Kingdom. &#x27E8;hal-01945362&#x27E9;. <http://epubs.surrey.ac.uk/id/eprint/849086>
  4. Overview of ExpertLifeCLEF 2018: how far automated identification systems are from the best experts?
    Hervé Goëau, Pierre Bonnet, Alexis Joly
    CLEF: Conference and Labs of the Evaluation Forum, Sep 2018, Avignon, France. &#x27E8;hal-01913244&#x27E9;.
  5. Overview of LifeCLEF 2018: A Large-Scale Evaluation of Species Identification and Recommendation Algorithms in the Era of AI
    Alexis Joly, Hervé Goëau, Christophe Botella, Hervé Glotin, Pierre Bonnet, Willem-Pier Vellinga, Robert Planqué, Henning Müller
    CLEF: Cross-Language Evaluation Forum, Sep 2018, Avignon, France. pp.247-266, &#x27E8;10.1007/978-3-319-98932-7_24&#x27E9;. &#x27E8;hal-01913231&#x27E9;.
  6. Location-based species recommendation using co-occurrences and environment-GeoLifeCLEF 2018 challenge
    Benjamin Deneu, Maximilien Servajean, Christophe Botella, Alexis Joly
    CLEF: Conference and Labs of the Evaluation Forum, Sep 2018, Avignon, France. &#x27E8;hal-01913241&#x27E9;.
  7. How Can You Mend a Broken Inconsistent KBs in Existential Rules Using Argumentation
    Bruno Yun
    SSA: Summer School on Argumentation, Sep 2018, Varsovie, Poland. &#x27E8;hal-01940651&#x27E9;. <http://ssa2018.argdiap.pl/>
  8. Answering Top-k Queries over Outsourced Sensitive Data in the Cloud
    Sakina Mahboubi, Reza Akbarinia, Patrick Valduriez
    DEXA: Database and Expert Systems Applications, Sep 2018, Regensburg, Germany. pp.218-231, &#x27E8;10.1007/978-3-319-98809-2_14&#x27E9;. &#x27E8;lirmm-01886164&#x27E9;.
  9. Discovering Tight Space-Time Sequences
    Riccardo Campisano, Heraldo Borges, Fábio Porto, Fabio Perosi, Esther Pacitti, Florent Masseglia, Eduardo Ogasawara
    DaWaK: Data Warehousing and Knowledge Discovery, Sep 2018, Regensburg, Germany. pp.247-257, &#x27E8;10.1007/978-3-319-98539-8_19&#x27E9;. &#x27E8;hal-01925965&#x27E9;.
  10. Privacy-Preserving Top-k Query Processing in Distributed Systems
    Sakina Mahboubi, Reza Akbarinia, Patrick Valduriez
    Euro-Par: European Conference on Parallel and Distributed Computing, Aug 2018, Turin, Italy. pp.281-292, &#x27E8;10.1007/978-3-319-96983-1_20&#x27E9;. &#x27E8;lirmm-01886160&#x27E9;.
  11. Scientific Data Analysis Using Data-Intensive Scalable Computing: the SciDISC Project
    Patrick Valduriez, Marta Mattoso, Reza Akbarinia, Heraldo Borges, José Camata, Alvaro Coutinho, Daniel Gaspar, Noel Lemus, Ji Liu, Hermano Lustosa, Florent Masseglia, Fabricio Nogueira da Silva, Vitor Silva, Renan Souza, Kary Ocaña, Eduardo Ogasawara, Daniel Oliveira, Esther Pacitti, Fábio Porto, Dennis Shasha
    LADaS: Latin America Data Science Workshop, Aug 2018, Rio de Janeiro, Brazil. &#x27E8;lirmm-01867804&#x27E9;. <http://ceur-ws.org/Vol-2170>
  12. Computation of PDFs on Big Spatial Data: Problem & Architecture
    Ji Liu, Noel Lemus, Esther Pacitti, Fábio Porto, Patrick Valduriez
    LADaS: Latin America Data Science Workshop, Aug 2018, Rio de Janeiro, Brazil. pp.6. &#x27E8;lirmm-01867758&#x27E9;.
  13. Constellation Queries over Big Data
    Fábio Porto, Amir Khatibi, Joao Rittmeyer, Eduardo Ogasawara, Patrick Valduriez, Dennis Shasha
    SBBD: Simpósio Brasileiro de Banco de Dados, SBC, Aug 2018, Rio de Janeiro, Brazil. pp.85-96. &#x27E8;lirmm-01867833&#x27E9;.
  14. Rumo à Integração da Álgebra de Workflows com o Processamento de Consulta Relacional
    João Ferreira, Jorge Soares, Fábio Porto, Esther Pacitti, Rafaelli Coutinho, Eduardo Ogasawara
    SBBD: Simpósio Brasileiro de Banco de Dados, SBC, Aug 2018, Rio de Janeiro, Brazil. pp.205-210. &#x27E8;lirmm-01868556&#x27E9;.
  15. F ReeP: towards parameter recommendation in scientific workflows using preference learning
    Daniel Silva, Aline Paes, Esther Pacitti, Daniel de Oliveira
    SBBD: Simpósio Brasileiro de Banco de Dados, SBC, Aug 2018, Rio de Janeiro, Brazil. &#x27E8;lirmm-01868574&#x27E9;. <http://sbbd.org.br/2018>
  16. Detecçao de Anomalias Frequentes no Transporte Rodoviario Urbano
    Ana Cruz, João Ferreira, Diego Carvalho, Eduardo Mendes, Esther Pacitti, Rafaelli Coutinho, Fábio Porto, Eduardo Ogasawara
    SBBD: Simpósio Brasileiro de Banco de Dados, SBC, Aug 2018, Rio de Janeiro, Brazil. pp.271-276. &#x27E8;lirmm-01868597&#x27E9;.
  17. Point Pattern Search in Big Data
    Fabio Porto, Joao Rittmeyer, Eduardo Ogasawara, Alberto Krone-Martins, Patrick Valduriez, Dennis Shasha
    SSDBM: Scientific and Statistical Database Management, Jul 2018, Bozen-Bolzano, Italy. &#x27E8;10.1145/3221269.3221294&#x27E9;. &#x27E8;lirmm-01819290&#x27E9;. <10.1145/3221269.3221294>
  18. Multichannel Audio Modeling with Elliptically Stable Tensor Decomposition
    Mathieu Fontaine, Fabian-Robert Stöter, Antoine Liutkus, Umut Simsekli, Romain Serizel, Roland Badeau
    LVA ICA 2018 - 14th International Conference on Latent Variable Analysis and Signal Separation, Jul 2018, Surrey, United Kingdom. &#x27E8;lirmm-01766795&#x27E9;.
  19. The 2018 Signal Separation Evaluation Campaign
    Fabian-Robert Stöter, Antoine Liutkus, Nobutaka Ito
    LVA ICA: Latent Variable Analysis and Signal Separation, Jul 2018, Surrey, United Kingdom. &#x27E8;lirmm-01766791v2&#x27E9;. <http://cvssp.org/events/lva-ica-2018/>
  20. A Distributed Collaborative Filtering Algorithm Using Multiple Data Sources
    Mohamed Bouadjenek, Esther Pacitti, Maximilien Servajean, Florent Masseglia, Amr Abbadi
    DBKDA: Advances in Databases, Knowledge, and Data Applications, May 2018, Nice, France. &#x27E8;hal-01911684&#x27E9;. <https://www.iaria.org/conferences2018/DBKDA18.html>
  21. A Differentially Private Index for Range Query Processing in Clouds
    Cetin Sahin, Tristan Allard, Reza Akbarinia, Amr Abbadi, Esther Pacitti
    ICDE: International Conference on Data Engineering, Apr 2018, Paris, France. pp.857-868. &#x27E8;lirmm-01886725&#x27E9;.
  22. Interference reduction on full-length live recordings
    Diego Di Carlo, Antoine Liutkus, Ken Déguernel
    ICASSP 2018 - IEEE International Conference on Acoustics, Speech, and Signal Processing, Apr 2018, Calgary, Canada. pp.736-740, &#x27E8;10.1109/ICASSP.2018.8462621&#x27E9;. &#x27E8;hal-01713889&#x27E9;.
  23. Blind Source Separation Using Mixtures of Alpha-Stable Distributions
    Nicolas Keriven, Antoine Deleforge, Antoine Liutkus
    ICASSP 2018 - IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2018, Calgary, Canada. pp.771-775, &#x27E8;10.1109/ICASSP.2018.8462095&#x27E9;. &#x27E8;hal-01633215v3&#x27E9;.
  24. Alpha-stable low-rank plus residual decomposition for speech enhancement
    Umut Simsekli, Halil Erdogan, Simon Leglaive, Antoine Liutkus, Roland Badeau, Gaël Richard
    ICASSP 2018 - IEEE International Conference on Acoustics, Speech, and Signal Processing, Apr 2018, Calgary, Canada. pp.651-655, &#x27E8;10.1109/ICASSP.2018.8461539&#x27E9;. &#x27E8;hal-01714909&#x27E9;.
  25. Audio source separation with magnitude priors: the BEADS model
    Antoine Liutkus, Christian Rohlfing, Antoine Deleforge
    ICASSP 2018 – IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2018, Calgary, Canada. pp.1-5, &#x27E8;10.1109/ICASSP.2018.8462515&#x27E9;. &#x27E8;hal-01713886v2&#x27E9;.
  26. Maximally Informative k-Itemset Mining from Massively Distributed Data Streams
    Mehdi Zitouni, Reza Akbarinia, Sadok Ben Yahia, Florent Masseglia
    SAC: Symposium on Applied Computing, Apr 2018, Pau, France. pp.1-10. &#x27E8;hal-01711990&#x27E9;.

2017

  1. DPiSAX: Massively Distributed Partitioned iSAX
    Djamel-Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Themis Palpanas
    ICDM: International Conference on Data Mining, Nov 2017, New Orleans, United States. pp.1-6, &#x27E8;10.1109/ICDM.2017.151&#x27E9;. &#x27E8;lirmm-01620125&#x27E9;.
  2. Querying Key-Value Stores Under Simple Semantic Constraints : Rewriting and Parallelization
    Olivier Rodriguez, Corentin Colomier, Cecilie Rivière, Reza Akbarinia, Federico Ulliana
    BDA: Gestion de Données — Principes, Technologies et Applications, Nov 2017, Nancy, France. &#x27E8;lirmm-01620207&#x27E9;. <https://project.inria.fr/bda2017/>
  3. Efficient Scheduling of Scientific Workflows using Hot Metadata in a Multisite Cloud
    Ji Liu, Luis Pineda-Morales, Esther Pacitti, Alexandru Costan, Patrick Valduriez, Gabriel Antoniu, Marta Mattoso
    BDA: Gestion de Données — Principes, Technologies et Applications, Nov 2017, Nancy, France. pp.13. &#x27E8;lirmm-01620231v2&#x27E9;.
  4. Massively Distributed Environments and Closed Itemset Mining: The DCIM Approach
    Mehdi Zitouni, Reza Akbarinia, Sadok Ben Yahia, Florent Masseglia
    BDA: Gestion de Données — Principes, Technologies et Applications, Nov 2017, Nancy, France. pp.1-15. &#x27E8;lirmm-01620354&#x27E9;.
  5. End-to-end Graph Mapper
    Benjamin Billet, Mickaël Jurret, Didier Parigot, Patrick Valduriez
    BDA: Gestion de Données — Principes, Technologies et Applications, Nov 2017, Nancy, France. &#x27E8;lirmm-01620239&#x27E9;. <https://project.inria.fr/bda2017/>
  6. Tracking of Online Parameter Fine-tuning in Scientific Workflows
    Renan Souza, Vitor Silva, José Camata, Alvaro Coutinho, Patrick Valduriez, Marta Mattoso
    WORKS: Workflows in Support of Large-scale Science, Nov 2017, Denver, United States. &#x27E8;lirmm-01620974&#x27E9;.
  7. TARS: An Array Model with Rich Semantics for Multidimensional Data
    Hermano Lustosa, Noel Lemus, Fabio Porto, Patrick Valduriez
    ER FORUM 2017: Conceptual Modeling : Research In Progress, Nov 2017, Valencia, Spain. &#x27E8;lirmm-01620376&#x27E9;.
  8. Pl@ntNet -My Business
    Alexis Joly, Pierre Bonnet, Antoine Affouard, Jean-Christophe Lombardo, Hervé Goëau
    MM: Multimedia, Oct 2017, Mountain View, United States. pp.1-11. &#x27E8;hal-01638263&#x27E9;.
  9. RadiusSketch: Massively Distributed Indexing of Time Series
    Djamel-Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Dennis Shasha
    DSAA: Data Science and Advanced Analytics, Oct 2017, Tokyo, Japan. pp.1-10. &#x27E8;lirmm-01620154&#x27E9;.
  10. Spark Scalability Analysis in a Scientific Workflow
    Renan Souza, Vitor Silva, Pedro Miranda, Alexandre Lima, Patrick Valduriez, Marta Mattoso
    SBBD: Simpósio Brasileiro de Banco de Dados, Oct 2017, Uberlandia, Brazil. pp.1-6. &#x27E8;lirmm-01620161&#x27E9;.
  11. Automated Herbarium Specimen Identification using Deep Learning
    Jose Carranza-Rojas, Alexis Joly, Pierre Bonnet, Hervé Goëau, Erick Mata-Montero
    TDWG: Biodiversity Information Standards, Oct 2017, Ottawa, Canada. &#x27E8;10.3897/tdwgproceedings.1.20302&#x27E9;. &#x27E8;hal-01629142&#x27E9;. <10.3897/tdwgproceedings.1.20302>
  12. LifeCLEF Bird Identification Task 2017
    Herve Goeau, Hervé Glotin, Willem-Pier Vellinga, Robert Planqué, Alexis Joly
    CLEF 2017 - Conference and Labs of the Evaluation Forum, Sep 2017, Dublin, Ireland. pp.1-9. &#x27E8;hal-01629175&#x27E9;.
  13. Plant identification based on noisy web data: the amazing performance of deep learning (LifeCLEF 2017)
    Herve Goeau, Pierre Bonnet, Alexis Joly
    CLEF 2017 - Conference and Labs of the Evaluation Forum, Sep 2017, Dublin, Ireland. pp.1-13. &#x27E8;hal-01629183&#x27E9;.
  14. LifeCLEF 2017 Lab Overview: Multimedia Species Identification Challenges
    Alexis Joly, Hervé Goëau, Hervé Glotin, Concetto Spampinato, Pierre Bonnet, Willem-Pier Vellinga, Jean-Christophe Lombardo, Robert Planque, Simone Palazzo, Henning Müller
    CLEF: Conference and Labs of the Evaluation forum, Sep 2017, Dublin, Ireland. pp.255-274, &#x27E8;10.1007/978-3-319-65813-1_24&#x27E9;. &#x27E8;hal-01629191&#x27E9;.
  15. TARDIS: Optimal Execution of Scientific Workflows in Apache Spark
    Daniel Gaspar, Fabio Porto, Reza Akbarinia, Esther Pacitti
    DaWaK: Data Warehousing and Knowledge Discovery, Aug 2017, Lyon, France. pp.74-87, &#x27E8;10.1007/978-3-319-64283-3_6&#x27E9;. &#x27E8;lirmm-01620060&#x27E9;.
  16. Pre-processing and Indexing techniques for Constellation Queries in Big Data
    Amir Khatibi, Fabio Porto, Joao Rittmeyer, Eduardo Ogasawara, Patrick Valduriez, Dennis Shasha
    DaWaK: Data Warehousing and Knowledge Discovery, Aug 2017, Lyon, France. pp.164-172, &#x27E8;10.1007/978-3-319-64283-3_12&#x27E9;. &#x27E8;lirmm-01620398&#x27E9;.
  17. Going deeper in the automated identification of Herbarium specimens
    Pierre Bonnet, Alexis Joly, Hervé Goëau, Jean-Christophe Lombardo, Antoine Affouard, Sen Wang, Rémi Knaff, Jean-François Molino, Daniel Barthélémy
    Botany 2017 - Botanical Crossroads, Jun 2017, Forth Worth, Texas, United States. &#x27E8;hal-01837387&#x27E9;.
  18. Massively Distributed Environments and Closed Itemset Mining: The DCIM Approach
    Mehdi Zitouni, Reza Akbarinia, Sadok Ben Yahia, Florent Masseglia
    CAiSE: Advanced Information Systems Engineering, Jun 2017, Essen, Germany. pp.231-246, &#x27E8;10.1007/978-3-319-59536-8_15&#x27E9;. &#x27E8;lirmm-01620238&#x27E9;.
  19. Pl@ntNet app in the era of deep learning
    Antoine Affouard, Hervé Goëau, Pierre Bonnet, Jean-Christophe Lombardo, Alexis Joly
    nnet, Jean-Christophe Lombardo, Alexis Joly. Pl@ntNet app in the era of deep learning. ICLR: International Conference on Learning Representations, Apr 2017, Toulon, France. pp.1-6. &#x27E8;hal-01629195&#x27E9;.

2016

  1. Managing Hot Metadata for Scientific Workflows on Multisite Clouds
    Luis Pineda-Morales, Ji Liu, Alexandru Costan, Esther Pacitti, Gabriel Antoniu, Patrick Valduriez, Marta Mattoso
    Big Data, Dec 2016, Washington, DC, United States. pp.390-397, &#x27E8;10.1109/BigData.2016.7840628&#x27E9;. &#x27E8;hal-01395715&#x27E9;.
  2. Benchmarking Polystores: the CloudMdsQL Experience
    Boyan Kolev, Raquel Pau, Oleksandra Levchenko, Patrick Valduriez, Ricardo Jiménez-Peris, José Pereira
    Big Data, Dec 2016, Washington, DC, United States. pp.2574-2579, &#x27E8;10.1109/BigData.2016.7840899&#x27E9;. &#x27E8;lirmm-01415582&#x27E9;.
  3. Demonstration of the CloudMdsQL Multistore System
    Boyan Kolev, Carlyna Bondiombouy, Patrick Valduriez, Ricardo Jiménez-Peris, Raquel Spain, José Pereira
    BDA: Gestion de Données — Principes, Technologies et Applications, Nov 2016, Poitiers, France. &#x27E8;lirmm-01408621&#x27E9;. <https://bda2016.ensma.fr/>
  4. Privacy Preserving Query Processing in the Cloud
    Sakina Mahboubi, Reza Akbarinia, Patrick Valduriez
    BDA: Gestion de Données — Principes, Technologies et Applications, Nov 2016, Poitiers, France. &#x27E8;lirmm-01410395&#x27E9;. <https://bda2016.ensma.fr>
  5. Scientific Workflow Execution with Multiple Objectives in Multisite Clouds
    Ji Liu, Esther Pacitti, Patrick Valduriez, Daniel de Oliveira, Marta Mattoso
    BDA: Gestion de Données — Principes, Technologies et Applications, LIAS / ISAE-ENSMA, Poitiers, Nov 2016, Poitiers, France. &#x27E8;lirmm-01409092&#x27E9;. <https://bda2016.ensma.fr>
  6. Extending CloudMdsQL with MFR for Big Data Integration
    Carlyna Bondiombouy, Boyan Kolev, Patrick Valduriez, Oleksandra Levchenko
    BDA: Gestion de Données — Principes, Technologies et Applications, LIAS / ISAE-ENSMA, Poitiers, Nov 2016, Poitiers, France. &#x27E8;lirmm-01409104&#x27E9;. <https://bda2016.ensma.fr>
  7. Online Input Data Reduction in Scientific Workflows
    Renan Souza, Vítor Silva, Alvaro Coutinho, Patrick Valduriez, Marta Mattoso
    WORKS: Workflows in Support of Large-scale Science, Nov 2016, Salt Lake City, United States. &#x27E8;lirmm-01400538&#x27E9;. <http://works.cs.cardiff.ac.uk>
  8. ThePlantGame: Actively Training Human Annotators for Domain-specific Crowdsourcing
    Maximilien Servajean, Alexis Joly, Dennis Shasha, Julien Champ, Esther Pacitti
    MM: Multimedia, Oct 2016, Amsterdam, Netherlands. &#x27E8;hal-01373769&#x27E9;. <http://www.acmmm.org/2016/>
  9. Crowdsourcing Biodiversity Monitoring: How Sharing your Photo Stream can Sustain our Planet
    Alexis Joly, Hervé Goëau, Julien Champ, Samuel Dufour-Kowalski, Henning Müller, Pierre Bonnet
    MM: Multimedia, Oct 2016, Amsterdam, Netherlands. &#x27E8;hal-01373762&#x27E9;. <http://www.acmmm.org/2016/>
  10. LifeCLEF Bird Identification Task 2016: The arrival of Deep learning
    Hervé Goëau, Hervé Glotin, Willem-Pier Vellinga, Robert Planqué, Alexis Joly
    Working Notes of CLEF 2016 - Conference and Labs of the Evaluation forum, Sep 2016, Evora, Portugal. pp.440--449. &#x27E8;hal-01373779&#x27E9;.
  11. Floristic participation at LifeCLEF 2016 Plant Identification Task
    Julien Champ, Hervé Goëau, Alexis Joly
    CLEF 2016 - Conference and Labs of the Evaluation forum, Sep 2016, Évora, Portugal. pp.450--458. &#x27E8;hal-01373776&#x27E9;.
  12. Unsupervised Individual Whales Identification: Spot the Difference in the Ocean
    Alexis Joly, Jean-Christophe Lombardo, Julien Champ, Anjara Saloma
    Working Notes of CLEF 2016 - Conference and Labs of the Evaluation forum, Sep 2016, Evora, Portugal. pp.469--480. &#x27E8;hal-01373777&#x27E9;.
  13. Plant Identification in an Open-world (LifeCLEF 2016)
    Hervé Goëau, Pierre Bonnet, Alexis Joly
    CLEF 2016 - Conference and Labs of the Evaluation forum, Sep 2016, Évora, Portugal. pp.428--439. &#x27E8;hal-01373780&#x27E9;.
  14. LifeCLEF 2016: Multimedia Life Species Identification Challenges
    Alexis Joly, Hervé Goëau, Hervé Glotin, Concetto Spampinato, Pierre Bonnet, Willem-Pier Vellinga, Julien Champ, Robert Planqué, Simone Palazzo, Henning Müller
    CLEF: Conference and Labs of the Evaluation forum, Sep 2016, Evora, Portugal. pp.286-310, &#x27E8;10.1007/978-3-319-44564-9_26&#x27E9;. &#x27E8;hal-01373781&#x27E9;.
  15. Enhancing Energy Production with Exascale HPC Methods
    José Camata, José Cela, Danilo Costa, Alvaro Lga Coutinho, Daniel Fernández-Galisteo, Carmen Jimenez, Vadim Kourdioumov, Marta Mattoso, Rafael Mayo-García, Thomas Miras, José Moríñigo, Jorge Navarro, Philippe Navaux, Daniel de Oliveira, Manuel Rodríguez-Pascual, Vítor Silva, Renan Souza, Patrick Valduriez
    CARLA: Latin American High Performance Computing Conference, Aug 2016, Mexico City, Mexico. pp.233-246, &#x27E8;10.1007/978-3-319-57972-6_17&#x27E9;. &#x27E8;lirmm-01654914&#x27E9;.
  16. Scientific Workflow Scheduling with Provenance Support in Multisite Cloud
    Ji Liu, Esther Pacitti, Patrick Valduriez, Marta Mattoso
    VECPAR, Faculty of Engineering of the University of Porto, Portugal, Jun 2016, Porto, Portugal. pp.8. &#x27E8;lirmm-01342190&#x27E9;.
  17. The CloudMdsQL Multistore System
    Boyan Kolev, Carlyna Bondiombouy, Patrick Valduriez, Ricardo Jiménez-Peris, Raquel Pau, José Pereira
    ACM SIGMOD, Jun 2016, San Francisco, United States. &#x27E8;10.1145/2882903.2899400&#x27E9;. &#x27E8;lirmm-01288025&#x27E9;. <10.1145/2882903.2899400>
  18. Development of a knowledge system for Big Data: Case study to plant phenotyping data
    Luyen Le Ngoc, Anne Tireau, Aravind Venkatesan, Pascal Neveu, Pierre Larmande
    WIMS: Web Intelligence, Mining and Semantics, Mines Ales, Jun 2016, Nimes, France. &#x27E8;10.1145/2912845.2912869&#x27E9;. &#x27E8;hal-01411565&#x27E9;. <10.1145/2912845.2912869>
  19. Spatially Localized Visual Dictionary Learning
    Valentin Leveau, Alexis Joly, Olivier Buisson, Patrick Valduriez
    ICMR: International Conference on Multimedia Retrieval, Jun 2016, New York, United States. pp.367-370, &#x27E8;10.1145/2911996.2912070&#x27E9;. &#x27E8;hal-01373778&#x27E9;.
  20. Exposing French agronomic resources as Linked Open Data
    Aravind Venkatesan, Nordine El Hassouni, Florian Phillipe, Cyril Pommier, Hadi Quesneville, Manuel Ruiz, Pierre Larmande
    IN-OLIVE, Jun 2016, Montpellier, France. &#x27E8;hal-01411759&#x27E9;.
  21. A New Privacy-Preserving Solution for Clustering Massively Distributed Personal Times-Series
    Tristan Allard, Georges Hébrail, Florent Masseglia, Esther Pacitti
    ICDE: International Conference on Data Engineering, May 2016, Helsinki, Finland. &#x27E8;lirmm-01270268&#x27E9;. <http://icde2016.fi/>
  22. Design and Implementation of the CloudMdsQL Multistore System
    Boyan Kolev, Carlyna Bondiombouy, Oleksandra Levchenko, Patrick Valduriez, Ricardo Jimenez-Péris, Raquel Pau, Jose Pereira
    CLOSER: Cloud Computing and Services Science, Apr 2016, Roma, Italy. pp.352-359, &#x27E8;10.5220/0005923803520359&#x27E9;. &#x27E8;lirmm-01341172&#x27E9;.

2015

  1. Exposing French agronomic resources as Linked Open Data
    Aravind Venkatesan, Nordine El Hassouni, Florian Philippe, Cyril Pommier, Hadi Quesneville, Manuel Ruiz, Pierre Larmande
    SWAT4LS: Semantic Web Applications and Tools for Life Sciences, Dec 2015, Cambridge, United Kingdom. &#x27E8;lirmm-01274884&#x27E9;. <http://ceur-ws.org/Vol-1546/>
  2. Managing Simulation Data with Multidimensional Arrays
    Hermano Lustosa, Fabio Porto, Ramon Costa, Pablo Blanco, Patrick Valduriez
    SBBD: Simpósio Brasileiro de Banco de Dados, Centro Federal de Educa‹o Tecnol—gica Celso Suckow da Fonseca (CEFET-RJ), Brazil; Laborat—rio Nacional de Computa‹o Cient’fica (LNCC), Oct 2015, Petropolis, Brazil. &#x27E8;lirmm-01184265&#x27E9;. <http://dexl.lncc.br/sbbd2015/>
  3. Query Processing in Cloud Multistore Systems
    Carlyna Bondiombouy
    BDA: Gestion de Données — Principes, Technologies et Applications, Sep 2015, Île de Porquerolles, France. &#x27E8;lirmm-01181253&#x27E9;. <http://bda2015.univ-tln.fr>
  4. Ontology-based services and knowledge management in the Agronomic Domain
    Pierre Larmande
    RDA: Research Data Alliance, Sep 2015, Paris, France. &#x27E8;lirmm-01274693&#x27E9;. <https://rd-alliance.org/plenary-meetings/rda-sixth-plenary-meeting.html>
  5. LifeCLEF 2015: Multimedia Life Species Identification Challenges
    Alexis Joly, Hervé Goëau, Hervé Glotin, Concetto Spampinato, Pierre Bonnet, Willem-Pier Vellinga, Robert Planqué, Andreas Rauber, Simone Palazzo, Bob Fisher, Henning Müller
    CLEF: Conference and Labs of the Evaluation forum, Sep 2015, Toulouse, France. pp.462-483, &#x27E8;10.1007/978-3-319-24027-5_46&#x27E9;. &#x27E8;hal-01182782&#x27E9;.
  6. LifeCLEF Bird Identification Task 2015
    Hervé Goëau, Hervé Glotin, Willem-Pier Vellinga, Robert Planqué, Andreas Rauber, Alexis Joly
    CLEF: Conference and Labs of the Evaluation forum, Sep 2015, toulouse, France. &#x27E8;hal-01182796&#x27E9;. <http://ceur-ws.org/Vol-1391/>
  7. LifeCLEF Plant Identification Task 2015
    Hervé Goëau, Pierre Bonnet, Alexis Joly
    CLEF: Conference and Labs of the Evaluation forum, Sep 2015, Toulouse, France. &#x27E8;hal-01182795&#x27E9;. <http://ceur-ws.org/Vol-1391/>
  8. A comparative study of fine-grained classification methods in the context of the LifeCLEF plant identification challenge 2015
    Julien Champ, Titouan Lorieul, Maximilien Servajean, Alexis Joly
    CLEF: Conference and Labs of the Evaluation forum, Sep 2015, Toulouse, France. &#x27E8;hal-01182788&#x27E9;. <http://ceur-ws.org/Vol-1391/>
  9. Shared nearest neighbors match kernel for bird songs identification -LifeCLEF 2015 challenge
    Alexis Joly, Valentin Leveau, Julien Champ, Olivier Buisson
    CLEF: Conference and Labs of the Evaluation forum, Sep 2015, Toulouse, France. &#x27E8;hal-01182784&#x27E9;. <http://ceur-ws.org/Vol-1391/>
  10. Integrating Big Data and Relational Data with a Functional SQL-like Query Language
    Carlyna Bondiombouy, Boyan Kolev, Oleksandra Levchenko, Patrick Valduriez
    Globe, Sep 2015, Valencia, Spain. pp.170-185, &#x27E8;10.1007/978-3-319-22849-5_13&#x27E9;. &#x27E8;lirmm-01181242&#x27E9;.
  11. An Efficient Solution for Processing Skewed MapReduce Jobs
    Reza Akbarinia, Miguel Liroz-Gistau, Divyakant Agrawal, Patrick Valduriez
    Globe, Sep 2015, Valencia, Spain. pp.417-429, &#x27E8;10.1007/978-3-319-22852-5_35&#x27E9;. &#x27E8;lirmm-01162359&#x27E9;.
  12. A Prime Number Based Approach for Closed Frequent Itemset Mining in Big Data
    Mehdi Zitouni, Reza Akbarinia, Sadok Ben Yahia, Florent Masseglia
    DEXA: Database and Expert Systems Applications, Sep 2015, Valencia, Spain. pp.509-516, &#x27E8;10.1007/978-3-319-22849-5_35&#x27E9;. &#x27E8;lirmm-01169606&#x27E9;.
  13. Data Partitioning for Fast Mining of Frequent Itemsets in Massively Distributed Environments
    Saber Salah, Reza Akbarinia, Florent Masseglia
    DEXA: Database and Expert Systems Applications, Sep 2015, Valencia, Spain. &#x27E8;lirmm-01169603&#x27E9;. <http://www.dexa.org>
  14. Fast Parallel Mining of Maximally Informative k-Itemsets in Big Data
    Saber Salah, Reza Akbarinia, Florent Masseglia
    ICDM: International Conference on Data Mining, Aug 2015, Atlantic city, United States. pp.359-368, &#x27E8;10.1109/ICDM.2015.86&#x27E9;. &#x27E8;lirmm-01187275&#x27E9;.
  15. When sharing computer science with everyone also helps avoiding digital prejudices.
    Marie Duflot, Martin Quinson, Florent Masseglia, Didier Roy, Julien Vaubourg, Thierry Viéville
    Escape computer dirty magic: learn Scratch !. Scratch2015AMS, Aug 2015, Amsterdam, Netherlands. &#x27E8;hal-01154767&#x27E9;.
  16. On Term Selection Techniques for Patent Prior Art Search
    Mona Golestan Far, Scott Sanner, Mohamed Reda Bouadjenek, Gabriela Ferraro, David Hawking
    SIGIR: Research and Development in Information Retrieval, Aug 2015, Santiago, Chile. &#x27E8;10.1145/2766462.2767801&#x27E9;. &#x27E8;lirmm-01163055&#x27E9;. <10.1145/2766462.2767801>
  17. Aggregation-Aware Compression of Probabilistic Streaming Time Series
    Reza Akbarinia, Florent Masseglia
    MLDM: Machine Learning and Data Mining, Jul 2015, Hamburg, Germany. pp.232-247, &#x27E8;10.1007/978-3-319-21024-7_16&#x27E9;. &#x27E8;lirmm-01162366&#x27E9;.
  18. Optimizing the Data-Process Relationship for Fast Mining of Frequent Itemsets in MapReduce
    Saber Salah, Reza Akbarinia, Florent Masseglia
    MLDM: Machine Learning and Data Mining, Jul 2015, Hamburg, Germany. pp.217-231, &#x27E8;10.1007/978-3-319-21024-7_15&#x27E9;. &#x27E8;lirmm-01171555&#x27E9;.
  19. Towards efficient data integration and knowledge management in the Agronomic domain
    Aravind Venkatesan, Nordine El Hassouni, Florian Phillipe, Cyril Pommier, Hadi Quesneville, Manuel Ruiz, Pierre Larmande
    APIA: Applications Pratiques de l'Intelligence Artificielle , Jul 2015, Rennes, France. &#x27E8;hal-01176903&#x27E9;. <http://pfia2015.inria.fr/actes/index.php?procpage=apia>
  20. OpenAlea: Scientific Workflows Combining Data Analysis and Simulation
    Christophe Pradal, Christian Fournier, Patrick Valduriez, Sarah Cohen-Boulakia
    SSDBM: Scientific and Statistical Database Management, Jun 2015, San Diego, United States. &#x27E8;10.1145/2791347.2791365&#x27E9;. &#x27E8;hal-01166298&#x27E9;. <10.1145/2791347.2791365>
  21. Kernelizing Spatially Consistent Visual Matches for Fine-Grained Classification
    Valentin Leveau, Alexis Joly, Olivier Buisson, Patrick Valduriez
    ICMR: International Conference on Multimedia Retrieval, Jun 2015, Shangai, China. pp.155-162, &#x27E8;10.1145/2671188.2749328&#x27E9;. &#x27E8;hal-01145988&#x27E9;.
  22. DigInPix: Visual Named-Entities Identification in Images and Videos
    Pierre Letessier, Nicolas Hervé, Alexis Joly, Hakim Nabi, Mathieu Derval, Olivier Buisson
    ICMR: International Conference on Multimedia Retrieval, Jun 2015, Shanghai, China. pp.661-664, &#x27E8;10.1145/2671188.2749369&#x27E9;. &#x27E8;hal-01182780&#x27E9;.
  23. A Study of Query Reformulation for Patent Prior Art Search with Partial Patent Applications
    Mohamed Reda Bouadjenek, Scott Sanner, Gabriela Ferraro
    ICAIL: International Conference on Artificial Intelligence and Law, Jun 2015, San Diego, United States. pp.23-32, &#x27E8;10.1145/2746090.2746092&#x27E9;. &#x27E8;lirmm-01134828&#x27E9;.
  24. Chiaroscuro: Transparency and Privacy for Massive Personal Time-Series Clustering
    Tristan Allard, Georges Hébrail, Florent Masseglia, Esther Pacitti
    ACM SIGMOD, May 2015, Melbourne, Australia. pp.779-794, &#x27E8;10.1145/2723372.2749453&#x27E9;. &#x27E8;hal-01136686&#x27E9;.
  25. Data-intensive HPC: opportunities and challenges
    Patrick Valduriez
    BDEC: Big Data and Extreme-scale Computing, Barcelona Supercomputing Center, Jan 2015, Barcelone, Spain. &#x27E8;lirmm-01184018&#x27E9;.

2014

  1. Recognizing Thousands of Legal Entities through Instance-based Visual Classification
    Valentin Leveau, Alexis Joly, Olivier Buisson, Pierre Letessier, Patrick Valduriez
    MM: Multimedia, Nov 2014, Orlando, FL, United States. &#x27E8;10.1145/2647868.2655038&#x27E9;. &#x27E8;hal-01077508&#x27E9;. <10.1145/2647868.2655038>
  2. Fine-grained Visual Faceted Search
    Julien Champ, Alexis Joly, Bonnet Pierre
    MM: Multimedia, Nov 2014, Orlando, FL, United States. pp.721-722, &#x27E8;10.1145/2647868.2654875&#x27E9;. &#x27E8;hal-01088822&#x27E9;.
  3. Layer Decomposition: An Effective Structure-based Approach for Scientific Workflow Similarity
    Johannes Starlinger, Sarah Cohen-Boulakia, Sanjeev Khanna, Susan Davidson, Ulf Leser
    IEEE e-Science conference, Oct 2014, Guarujá, Brazil. &#x27E8;hal-01066076&#x27E9;.
  4. NACluster: A Non-Supervised Clustering Algorithm for Matching Multi Catalogues
    Vinicius P. Freire, José A. F. de Macêdo, Fábio Porto, Reza Akbarinia
    IEEE e-Science Workshop, Oct 2014, Guarujá, SP, Brazil. &#x27E8;lirmm-01076107&#x27E9;. <http://escience.ime.usp.br/preliminary-program/accepted-papers/accepted-papers-workshops>
  5. PlantRT : a Distributed Recommendation Tool for Citizen Science
    Maximilien Servajean, Esther Pacitti, Miguel Liroz-Gistau, Alexis Joly, Julien Champ
    BDA: Gestion de Données — Principes, Technologies et Applications, Oct 2014, Autrans, France. pp.48-50. &#x27E8;hal-01163819&#x27E9;.
  6. Compression de flux de données probabilistes attentive à l'agrégation
    Reza Akbarinia, Florent Masseglia
    BDA: Gestion de Données — Principes, Technologies et Applications, Oct 2014, Autrans, France. &#x27E8;lirmm-01091870&#x27E9;. <http://bda2014.imag.fr>
  7. Exploiting Diversification in Distributed Recommendation
    Maximilien Servajean, Esther Pacitti, Miguel Liroz-Gistau, Sihem Amer-Yahia, Amr El Abbadi
    BDA: Gestion de Données — Principes, Technologies et Applications, IMAG, Oct 2014, Autrans, France. &#x27E8;lirmm-01177564&#x27E9;. <http://bda2014.imag.fr>
  8. Multisite Management of Data-intensive Scientific Workflows in the Cloud
    Ji Liu
    BDA: Gestion de Données — Principes, Technologies et Applications, Oct 2014, Autrans, France. pp.28-30. &#x27E8;hal-01169960&#x27E9;.
  9. Instance-based bird species identication with undiscriminant features pruning - LifeCLEF 2014
    Alexis Joly, Julien Champ, Olivier Buisson
    CLEF: Conference and Labs of the Evaluation Forum, Sep 2014, Sheffield, United Kingdom. &#x27E8;hal-01088798&#x27E9;. <http://clef2014.clef-initiative.eu>
  10. LifeCLEF Bird Identification Task 2014
    Hervé Goëau, Hervé Glotin, Willem-Pier Vellinga, Robert Planqué, Andreas Rauber, Alexis Joly
    CLEF: Conference and Labs of the Evaluation Forum, Sep 2014, Sheffield, United Kingdom. &#x27E8;hal-01088829&#x27E9;. <http://clef2014.clef-initiative.eu>
  11. LifeCLEF 2014: Multimedia Life Species Identification Challenges
    Alexis Joly, Hervé Goëau, Hervé Glotin, Concetto Spampinato, Pierre Bonnet, Willem-Pier Vellinga, Robert Planque, Andreas Rauber, Bob Fisher, Henning Müller
    CLEF: Conference and Labs of the Evaluation forum, Sep 2014, Sheffield, United Kingdom. pp.229-249, &#x27E8;10.1007/978-3-319-11382-1_20&#x27E9;. &#x27E8;hal-01075770&#x27E9;.
  12. Exploiting Diversification in Gossip-Based Recommendation
    Maximilien Servajean, Esther Pacitti, Miguel Liroz-Gistau, Sihem Amer-Yahia, Amr El Abbadi
    Globe, Sep 2014, Munich, Germany. pp.25-36, &#x27E8;10.1007/978-3-319-10067-8_3&#x27E9;. &#x27E8;lirmm-01088730&#x27E9;.
  13. Scientific Workflow Partitioning in Multi-site Clouds
    Ji Liu, Esther Pacitti, Patrick Valduriez, Vitor Silva Souza, Marta Mattoso
    Euro-Par: European Conference on Parallel Processing, Aug 2014, Porto, Portugal. pp.105-116, &#x27E8;10.1007/978-3-319-14325-5_10&#x27E9;. &#x27E8;lirmm-01073613&#x27E9;.
  14. The role of hydraulics FSPMs in the context of root breeding : a case study on Pearl Millet
    Adama Ndour, Christophe Pradal, Vincent Vadez, Sixtine Passot, Yann Guédon, Laurent Laplaze, Mikael Lucas
    EGU: European Geosciences Union, Apr 2014, Vienne, Austria. &#x27E8;hal-01780939&#x27E9;.
  15. LifeCLEF: Multimedia Life Species Identification
    Alexis Joly, Robert Planque, Concetto Spampinato, Henning Müller, Hervé Goëau, Andreas Rauber, Bonnet Pierre, Willem-Pier Vellinga, Robert B. Fisher, Hervé Glotin
    EMR: Environmental Multimedia Retrieval, Apr 2014, Glasgow, United Kingdom. &#x27E8;hal-01088812&#x27E9;. <http://ceur-ws.org/Vol-1222/>
  16. Pl@ntNet Mobile 2014: Android port and new features
    Hervé Goëau, Bonnet Pierre, Alexis Joly, Antoine Affouard, Vera Bakić, Julien Barbe, Samuel Dufour-Kowalski, Souheil Selmi, Yahiaoui Itheri, Christel Vignau, Daniel Barthelemy, Nozha Boujemaa
    ICMR: International Conference on Multimedia Retrieval, Apr 2014, Glasgow, United Kingdom. pp.527-530, &#x27E8;10.1145/2578726.2582618&#x27E9;. &#x27E8;hal-01088819&#x27E9;.

Mots-clés

Big data, Données scientifiques, Gestion de données distribuées et parallèles, Analyse et fouille de données, Recommandation et recherche de contenus, Communautés en ligne, Workflows scientifiques, Intégration, Confidentialité, Recherche d’information par contenu, P2P, Grid, Cloud

Dernière mise à jour le 01/02/2019