EN FR
EN FR


previous Previous | up Home


Bibliography

Major publications by the team in recent years
  • 1T. Allard, G. Hébrail, F. Masseglia, E. Pacitti.

    Chiaroscuro: Transparency and Privacy for Massive Personal Time-Series Clustering, in: 34th International ACM Conference on Management of Data (ACM SIGMOD), Melbourne, Australia, ACM SIGMOD, May 2015. [ DOI : 10.1145/2723372.2749453 ]

    https://hal.inria.fr/hal-01136686
  • 2A. Joly, P. Bonnet, H. Goëau, J. Barbe, S. Selmi, J. Champ, S. Dufour-Kowalski, A. Affouard, J. Carré, J.-F. Molino, N. Boujemaa, D. Barthélémy.

    A look inside the Pl@ntNet experience, in: Multimedia Systems, 2015, 16 p. [ DOI : 10.1007/s00530-015-0462-9 ]

    https://hal.inria.fr/hal-01182775
  • 3A. Joly, H. Goeau, P. Bonnet, V. Bakic, J. Barbe, S. Selmi, I. Yahiaoui, J. Carré, E. Mouysset, J.-F. Molino, N. Boujemaa, D. Barthélémy.

    Interactive plant identification based on social image data, in: Ecological Informatics, 2013. [ DOI : 10.1016/j.ecoinf.2013.07.006 ]

    http://www.sciencedirect.com/science/article/pii/S157495411300071X
  • 4B. Kolev, P. Valduriez, C. Bondiombouy, R. Jimenez-Peris, R. Pau, J. O. Pereira.

    CloudMdsQL: Querying Heterogeneous Cloud Data Stores with a Common Language, in: Distributed and Parallel Databases, December 2016, vol. 34, no 4, pp. 463-503. [ DOI : 10.1007/s10619-015-7185-y ]

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01184016
  • 5M. Liroz-Gistau, R. Akbarinia, D. Agrawal, P. Valduriez.

    FP-Hadoop: Efficient Processing of Skewed MapReduce Jobs, in: Information Systems, 2016, vol. 60, pp. 69-84. [ DOI : 10.1016/j.is.2016.03.008 ]

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01377715
  • 6J. Liu, E. Pacitti, P. Valduriez, D. De Oliveira, M. Mattoso.

    Multi-Objective Scheduling of Scientific Workflows in Multisite Clouds, in: Future Generation Computer Systems, 2016, vol. 63, pp. 76–95. [ DOI : 10.1016/j.future.2016.04.014 ]

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01342203
  • 7H. Lustosa, F. Porto, P. Blanco, P. Valduriez.

    Database System Support of Simulation Data, in: Proceedings of the VLDB Endowment (PVLDB), September 2016, vol. 9, no 13, pp. 1329-1340.

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01363738
  • 8E. Pacitti, R. Akbarinia, M. El Dick.

    P2P Techniques for Decentralized Applications, Morgan & Claypool Publishers, 2012, 104 p.

    http://hal.inria.fr/lirmm-00748635
  • 9S. Salah, R. Akbarinia, F. Masseglia.

    Fast Parallel Mining of Maximally Informative k-Itemsets in Big Data, in: IEEE International Conference on Data Mining (ICDM), Atlantic city, United States, August 2015.

    http://hal-lirmm.ccsd.cnrs.fr/lirmm-01187275
  • 10M. Servajean, R. Akbarinia, E. Pacitti, S. Amer-Yahia.

    Profile Diversity for Query Processing using User Recommendations, in: Information Systems, March 2015, vol. 48, pp. 44-63. [ DOI : 10.1016/j.is.2014.09.001 ]

    http://hal-lirmm.ccsd.cnrs.fr/lirmm-01079523
  • 11M. Servajean, A. Joly, D. Shasha, J. Champ, E. Pacitti.

    Crowdsourcing Thousands of Specialized Labels: A Bayesian Active Training Approach, in: IEEE Transactions on Multimedia, June 2017, vol. 19, no 6, pp. 1376 - 1391. [ DOI : 10.1109/TMM.2017.2653763 ]

    https://hal.archives-ouvertes.fr/hal-01629149
  • 12T. M. Özsu, P. Valduriez.

    Principles of Distributed Database Systems, third edition, Springer, 2011, 845 p.

    http://hal.inria.fr/hal-00640392/en
Publications of the year

Articles in International Peer-Reviewed Journals

  • 13J. Camata, V. Silva, P. Valduriez, M. Mattoso, A. L. G. A. Coutinho.

    In situ visualization and data analysis for turbidity currents simulation, in: Computers & Geosciences, January 2018, vol. 110, pp. 23-31. [ DOI : 10.1016/j.cageo.2017.09.013 ]

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620127
  • 14J. Carranza-Rojas, H. Goeau, P. Bonnet, E. Mata-Montero, A. Joly.

    Going deeper in the automated identification of Herbarium specimens, in: BMC Evolutionary Biology, December 2017, vol. 17, no 1, 181 p. [ DOI : 10.1186/s12862-017-1014-z ]

    https://hal.inria.fr/hal-01580070
  • 15S. Cohen-Boulakia, K. Belhajjame, O. Collin, J. Chopard, C. Froidevaux, A. Gaignard, K. Hinsen, P. Larmande, Y. Le Bras, F. Lemoine, F. Mareuil, H. Ménager, C. Pradal, C. Blanchet.

    Scientific workflows for computational reproducibility in the life sciences: Status, challenges and opportunities, in: Future Generation Computer Systems, 2017. [ DOI : 10.1016/j.future.2017.01.012 ]

    https://hal.archives-ouvertes.fr/hal-01516082
  • 16J. Liu, E. Pacitti, P. Valduriez, M. Mattoso.

    Scientific Workflow Scheduling with Provenance Data in a Multisite Cloud, in: Transactions on Large-Scale Data- and Knowledge-Centered Systems, 2017, vol. 33, pp. 80-112. [ DOI : 10.1109/IPDPS.2007.370305 ]

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620224
  • 17C. Pradal, S. Artzet, J. Chopard, D. Dupuis, C. Fournier, M. Mielewczik, V. Negre, P. Neveu, D. Parigot, P. Valduriez, S. Cohen-Boulakia.

    InfraPhenoGrid: A scientific workflow infrastructure for Plant Phenomics on the Grid, in: Future Generation Computer Systems, February 2017, vol. 67, pp. 341–353. [ DOI : 10.1016/j.future.2016.06.002 ]

    https://hal.inria.fr/hal-01336655
  • 18S. Salah, R. Akbarinia, F. Masseglia.

    A Highly Scalable Parallel Algorithm for Maximally Informative k-Itemset Mining, in: Knowledge and Information Systems (KAIS), January 2017.

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01288571
  • 19S. Salah, R. Akbarinia, F. Masseglia.

    Data placement in massively distributed environments for fast parallel mining of frequent itemsets, in: Knowledge and Information Systems (KAIS), 2017, vol. 53, no 1, pp. 207-237. [ DOI : 10.1007/s10115-017-1041-5 ]

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620383
  • 20M. Servajean, A. Joly, D. Shasha, J. Champ, E. Pacitti.

    Crowdsourcing Thousands of Specialized Labels: A Bayesian Active Training Approach, in: IEEE Transactions on Multimedia, June 2017, vol. 19, no 6, pp. 1376 - 1391. [ DOI : 10.1109/TMM.2017.2653763 ]

    https://hal.archives-ouvertes.fr/hal-01629149
  • 21V. J. Silva, J. J. Leite, J. J. Camata, D. De Oliveira, A. L. G. A. Coutinho, P. Valduriez, M. J. Mattoso.

    Raw data queries during data-intensive parallel workflow execution, in: Future Generation Computer Systems, January 2017, vol. 75, pp. 402-422. [ DOI : 10.1016/j.future.2017.01.016 ]

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01445219

International Conferences with Proceedings

  • 22B. Billet, M. Jurret, D. Parigot, P. Valduriez.

    End-to-end Graph Mapper, in: BDA: Conférence sur la Gestion de Données — Principes, Technologies et Applications, Nancy, France, November 2017.

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620239
  • 23J. Carranza-Rojas, A. Joly, P. Bonnet, H. Goëau, E. Mata-Montero.

    Automated Herbarium Specimen Identification using Deep Learning, in: TDWG 2017 - Annual Conference on Biodiversity Information Standards, Ottawa, Canada, October 2017. [ DOI : 10.3897/tdwgproceedings.1.20302 ]

    https://hal.archives-ouvertes.fr/hal-01629142
  • 24D. Gaspar, F. Porto, R. Akbarinia, E. Pacitti.

    TARDIS: Optimal Execution of Scientific Workflows in Apache Spark, in: DaWaK 2017: Data Warehousing and Knowledge Discovery, Lyon, France, LNCS, August 2017, no 10440, pp. 74-87. [ DOI : 10.1007/978-3-319-64283-3_6 ]

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620060
  • 25A. Joly, P. Bonnet, A. Affouard, J.-C. Lombardo, H. Goëau.

    Pl@ntNet -My Business, in: ACM Multimedia 2017, Mountain View, United States, October 2017, pp. 1-11.

    https://hal.inria.fr/hal-01638263
  • 26A. Joly, H. Goëau, H. Glotin, C. Spampinato, P. Bonnet, W.-P. Vellinga, J.-C. Lombardo, R. Planque, S. Palazzo, H. Müller.

    LifeCLEF 2017 Lab Overview: Multimedia Species Identification Challenges, in: CLEF: Cross-Language Evaluation Forum for European Languages, Dublin, Ireland, G. J. Jones, S. Lawless, J. Gonzalo, L. Kelly, L. Goeuriot, T. Mandl, L. Cappellato, N. Ferro (editors), Experimental IR Meets Multilinguality, Multimodality, and Interaction, Springer, September 2017, vol. LNCS, no 10456, pp. 255-274. [ DOI : 10.1007/978-3-319-65813-1_24 ]

    https://hal.archives-ouvertes.fr/hal-01629191
  • 27A. Khatibi, F. Porto, J. G. Rittmeyer, E. Ogasawara, P. Valduriez, D. Shasha.

    Pre-processing and Indexing techniques for Constellation Queries in Big Data, in: DaWaK 2017: 19th International Conference on Big Data Analytics and Knowledge Discovery, Lyon, France, Big Data Analytics and Knowledge Discovery, Springer, August 2017, no 10253, pp. 74-87.

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620398
  • 28J. Liu, L. Pineda-Morales, E. Pacitti, A. Costan, P. Valduriez, G. Antoniu, M. Mattoso.

    Efficient Scheduling of Scientific Workflows using Hot Metadata in a Multisite Cloud, in: BDA: Conférence sur la Gestion de Données — Principes, Technologies et Applications, Nancy, France, November 2017, 13 p.

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620231
  • 29H. Lustosa, N. Lemus, F. Porto, P. Valduriez.

    TARS: An Array Model with Rich Semantics for Multidimensional Data, in: ER FORUM 2017: Conceptual Modeling : Research In Progress, Valencia, Spain, November 2017.

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620376
  • 30O. Rodriguez, C. Colomier, C. Rivière, R. Akbarinia, F. Ulliana.

    Querying Key-Value Stores Under Simple Semantic Constraints : Rewriting and Parallelization, in: BDA: Conférence sur la Gestion de Données — Principes, Technologies et Applications ", Nancy, France, November 2017.

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620207
  • 31R. Souza, V. Silva, J. Camata, A. L. G. A. Coutinho, P. Valduriez, M. Mattoso.

    Tracking of Online Parameter Fine-tuning in Scientific Workflows, in: Workflows in Support of Large-Scale Science (WORKS), in conjunction with ACM/IEEE Supercomputing, Denver, United States, November 2017.

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620974
  • 33M. Zitouni, R. Akbarinia, S. Ben Yahia, F. Masseglia.

    Massively Distributed Environments and Closed Itemset Mining: The DCIM Approach, in: CAiSE: Advanced Information Systems Engineering, Essen, Germany, June 2017, vol. LNCS, no 10253, pp. 231-246. [ DOI : 10.1007/978-3-319-59536-8_15 ]

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620238

Conferences without Proceedings

  • 34A. Affouard, H. Goëau, P. Bonnet, J.-C. Lombardo, A. Joly.

    Pl@ntNet app in the era of deep learning, in: ICLR 2017 - Workshop Track - 5th International Conference on Learning Representations, Toulon, France, April 2017, pp. 1-6.

    https://hal.archives-ouvertes.fr/hal-01629195
  • 35H. Goeau, P. Bonnet, A. Joly.

    Plant identification based on noisy web data: the amazing performance of deep learning (LifeCLEF 2017), in: CLEF 2017 - Conference and Labs of the Evaluation Forum, Dublin, Ireland, September 2017, pp. 1-13.

    https://hal.archives-ouvertes.fr/hal-01629183
  • 36H. Goeau, H. Glotin, W.-P. Vellinga, R. Planqué, A. Joly.

    LifeCLEF Bird Identification Task 2017, in: CLEF 2017 - Conference and Labs of the Evaluation Forum, Dublin, Ireland, September 2017, pp. 1-9.

    https://hal.archives-ouvertes.fr/hal-01629175

Scientific Books (or Scientific Book chapters)

  • 37A. A. Nugraha, A. Liutkus, E. Vincent.

    Deep neural network based multichannel audio source separation, in: Audio Source Separation, Springer, 2017, forthcoming.

    https://hal.inria.fr/hal-01633858

Books or Proceedings Editing

  • 38L. Bellatreche, P. Valduriez, T. Morzy (editors)

    Advances in Databases and Information Systems, Elsevier, October 2017, vol. 70. [ DOI : 10.1016/j.is.2017.08.003 ]

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01630719
  • 39A. Hameurlain, J. Küng, R. Wagner, R. Akbarinia, E. Pacitti (editors)

    Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXIII, Springer, Berlin, Heidelberg, 2017, vol. LNCS, no 10430. [ DOI : 10.1007/978-3-662-55696-2 ]

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01624805

Internal Reports

Scientific Popularization

  • 42D.-E. Yagoubi, R. Akbarinia, F. Masseglia, T. Palpanas.

    DPiSAX: Massively Distributed Partitioned iSAX, in: ICDM 2017: IEEE International Conference on Data Mining, New Orleans, United States, November 2017, pp. 1-6.

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620125
  • 43D.-E. Yagoubi, R. Akbarinia, F. Masseglia, D. Shasha.

    RadiusSketch: Massively Distributed Indexing of Time Series, in: DSAA 2017: IEEE International Conference on Data Science and Advanced Analytics, Tokyo, Japan, October 2017, pp. 1-10.

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620154
  • 44M. Zitouni, R. Akbarinia, S. Ben Yahia, F. Masseglia.

    Massively Distributed Environments and Closed Itemset Mining: The DCIM Approach, in: BDA 2017: 33ème Conférence sur la Gestion de Données — Principes, Technologies et Applications, Nancy, France, November 2017, vol. 4, pp. 1-15. [ DOI : 10.1145/1837934.1837995 ]

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620354

Other Publications

  • 45N. Keriven, A. Deleforge, A. Liutkus.

    Blind Source Separation Using Mixtures of Alpha-Stable Distributions, November 2017, working paper or preprint.

    https://hal.inria.fr/hal-01633215
  • 46B. Kolev, O. Levchenko, F. Masseglia, R. Akbarinia, E. Pacitti, P. Valduriez.

    Highly Scalable Real-Time Analytics with CloudDBAppliance, October 2017, XLDB: Extremely Large Databases Conference, Poster.

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01632355


previous Previous | up Home