EN FR
EN FR


previous Previous | up Home


Bibliography

Major publications by the team in recent years
  • 1S. Abiteboul, P. Bourhis, V. Vianu.

    Explanations and Transparency in Collaborative Workflows, in: PODS 2018 - 37th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles Of Database Systems, Houston, Texas, United States, June 2018.

    https://hal.inria.fr/hal-01744978
  • 2A. Amarilli, F. Capelli, M. Monet, P. Senellart.

    Connecting Knowledge Compilation Classes and Width Parameters, in: Theory of Computing Systems, June 2019, https://arxiv.org/abs/1811.02944. [ DOI : 10.1007/s00224-019-09930-2 ]

    https://hal.inria.fr/hal-02163749
  • 3C. Bourgaux, A. Ozaki.

    Querying Attributed DL-Lite Ontologies Using Provenance Semirings, in: Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), Honolulu, United States, January 2019.

    https://hal.inria.fr/hal-02109645
  • 4F. Jacquemard, L. Segoufin, J. Dimino.

    FO2(<, +1, ~) on data trees, data tree automata and branching vector addition systems, in: Logical Methods in Computer Science, 2016, vol. 12, no 2.

    https://doi.org/10.2168/LMCS-12(2:3)2016
  • 5P. Lagrée, O. Cappé, B. Cautis, S. Maniu.

    Algorithms for Online Influencer Marketing, in: ACM Transactions on Knowledge Discovery from Data (TKDD), January 2019, vol. 13, no 1, pp. 1-30. [ DOI : 10.1145/3274670 ]

    https://hal.inria.fr/hal-01478788
  • 6M. Leclère, M.-L. Mugnier, M. Thomazo, F. Ulliana.

    A Single Approach to Decide Chase Termination on Linear Existential Rules, in: ICDT 2019 - International Conference on Database Theory, Lisbonne, Portugal, 2019. [ DOI : 10.4230/LIPIcs.ICDT.2019.15 ]

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-02148200
  • 7S. Maniu, R. Cheng, P. Senellart.

    An Indexing Framework for Queries on Probabilistic Graphs, in: ACM Trans. Datab. Syst, 2017.

    https://hal.inria.fr/hal-01437580
  • 8Y. Russac, C. Vernade, O. Cappé.

    Weighted Linear Bandits for Non-Stationary Environments, in: NeurIPS 2019 - 33rd Conference on Neural Information Processing Systems, Vancouver, Canada, December 2019, https://arxiv.org/abs/1909.09146.

    https://hal.inria.fr/hal-02291460
  • 9N. Schweikardt, L. Segoufin, A. Vigny.

    Enumeration for FO Queries over Nowhere Dense Graphs, in: PODS 2018 - Principles Of Database Systems, Houston, United States, June 2018.

    https://hal.inria.fr/hal-01895786
  • 10P. Senellart, L. Jachiet, S. Maniu, Y. Ramusat.

    ProvSQL: Provenance and Probability Management in PostgreSQL, in: Proceedings of the VLDB Endowment (PVLDB), August 2018, vol. 11, no 12, pp. 2034-2037. [ DOI : 10.14778/3229863.3236253 ]

    https://hal.inria.fr/hal-01851538
Publications of the year

Doctoral Dissertations and Habilitation Theses

Articles in International Peer-Reviewed Journals

  • 12S. Abiteboul, J. Stoyanovich.

    Transparency, Fairness, Data Protection, Neutrality: Data Management Challenges in the Face of New Regulation, in: Journal of data and information quality, 2019. [ DOI : 10.1145/3310231 ]

    https://hal.inria.fr/hal-02066516
  • 13A. Amarilli, M. L. Ba, D. Deutch, P. Senellart.

    Computing Possible and Certain Answers over Order-Incomplete Data, in: Theoretical Computer Science, 2019, vol. 797, pp. 42-76, https://arxiv.org/abs/1801.06396. [ DOI : 10.1016/j.tcs.2019.05.013 ]

    https://hal.inria.fr/hal-01891814
  • 14A. Amarilli, P. Bourhis, M. Monet, P. Senellart.

    Evaluating Datalog via Tree Automata and Cycluits, in: Theory of Computing Systems, 2019, vol. 63, no 7, pp. 1620-1678, https://arxiv.org/abs/1808.04663. [ DOI : 10.1007/s00224-018-9901-2 ]

    https://hal.inria.fr/hal-01891811
  • 15A. Amarilli, F. Capelli, M. Monet, P. Senellart.

    Connecting Knowledge Compilation Classes and Width Parameters, in: Theory of Computing Systems, June 2019, https://arxiv.org/abs/1811.02944. [ DOI : 10.1007/s00224-019-09930-2 ]

    https://hal.inria.fr/hal-02163749
  • 16M. Benedikt, P. Bourhis, G. Gottlob, P. Senellart.

    Monadic Datalog, Tree Validity, and Limited Access Containment, in: ACM Transactions on Computational Logic, October 2019, vol. 21, no 1, pp. 6:1-6:45. [ DOI : 10.1145/3344514 ]

    https://hal.inria.fr/hal-02307999
  • 17M. Crochemore, A. Héliou, G. Kucherov, L. Mouchard, S. Pissis, Y. Ramusat.

    Absent words in a sliding window with applications, in: Information and Computation, September 2019, 104461 p. [ DOI : 10.1016/j.ic.2019.104461 ]

    https://hal.archives-ouvertes.fr/hal-02414839
  • 18S. Holub, T. Masopust, M. Thomazo.

    On the Height of Towers of Subsequences and Prefixes, in: Information and Computation, April 2019. [ DOI : 10.1016/j.ic.2019.01.004 ]

    https://hal.inria.fr/hal-02269576
  • 19P. Lagrée, O. Cappé, B. Cautis, S. Maniu.

    Algorithms for Online Influencer Marketing, in: ACM Transactions on Knowledge Discovery from Data (TKDD), January 2019, vol. 13, no 1, pp. 1-30. [ DOI : 10.1145/3274670 ]

    https://hal.inria.fr/hal-01478788

Invited Conferences

  • 20P. Senellart.

    Provenance in Databases: Principles and Applications, in: RW 2019 : Reasoning Web Summer School, Bolzano, Italy, September 2019, pp. 104-109. [ DOI : 10.1007/978-3-030-31423-1_3 ]

    https://hal.inria.fr/hal-02293688

International Conferences with Proceedings

  • 21D. Basu, P. Senellart, S. Bressan.

    BelMan: An Information-Geometric Approach to Stochastic Bandits, in: ECML/PKDD - The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Würzburg, Germany, September 2019.

    https://hal.inria.fr/hal-02195539
  • 22M. Benedikt, P. Bourhis, L. Jachiet, M. Thomazo.

    Reasoning about disclosure in data integration in the presence of source constraints, in: IJCAI 2019 - 28th International Joint Conference on Artificial Intelligence, Macao, China, August 2019, https://arxiv.org/abs/1906.00624.

    https://hal.inria.fr/hal-02145369
  • 23C. Bourgaux, A. Ozaki.

    Querying Attributed DL-Lite Ontologies Using Provenance Semirings (Extended Abstract), in: DL 2019 - 32nd International Workshop on Description Logics, Oslo, Norway, June 2019.

    https://hal.inria.fr/hal-02152064
  • 24C. Bourgaux, A. Ozaki.

    Querying Attributed DL-Lite Ontologies Using Provenance Semirings, in: Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), Honolulu, United States, January 2019.

    https://hal.inria.fr/hal-02109645
  • 25J. Grange, L. Segoufin.

    Order-Invariant First-Order Logic over Hollow Trees, in: CSL 2020 - 28th annual conference of the European Association for Computer Science Logic, Barcelona, Spain, January 2020, vol. 23, pp. 1-23. [ DOI : 10.4230/LIPIcs.CSL.2020.23 ]

    https://hal.inria.fr/hal-02310749
  • 26N. Grosshans.

    The Power of Programs over Monoids in J, in: 14th International Conference on Language and Automata Theory and Applications (LATA 2020), Milan, Italy, March 2020, https://arxiv.org/abs/1912.07992.

    https://hal.archives-ouvertes.fr/hal-02414771
  • 27M. Leclère, M.-L. Mugnier, M. Thomazo, F. Ulliana.

    A Single Approach to Decide Chase Termination on Linear Existential Rules, in: ICDT 2019 - International Conference on Database Theory, Lisbonne, Portugal, 2019. [ DOI : 10.4230/LIPIcs.ICDT.2019.15 ]

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-02148200
  • 28S. Maniu, P. Senellart, S. Jog.

    An Experimental Study of the Treewidth of Real-World Graph Data, in: ICDT 2019 – 22nd International Conference on Database Theory, Lisbon, Portugal, March 2019, 18 p. [ DOI : 10.4230/LIPIcs.ICDT.2019.12 ]

    https://hal.inria.fr/hal-02087763
  • 29Y. Russac, C. Vernade, O. Cappé.

    Weighted Linear Bandits for Non-Stationary Environments, in: NeurIPS 2019 - 33rd Conference on Neural Information Processing Systems, Vancouver, Canada, December 2019, https://arxiv.org/abs/1909.09146.

    https://hal.inria.fr/hal-02291460
  • 30T. P. Tanon, C. Bourgaux, F. M. Suchanek.

    Learning How to Correct a Knowledge Base from the Edit History, in: World Wide Web Conference, San Francisco, United States, Proceedings of the 2019 World Wide Web Conference (WWW ’19), May 2019. [ DOI : 10.1145/3308558.3313584 ]

    https://hal-imt.archives-ouvertes.fr/hal-02066041

Scientific Books (or Scientific Book chapters)

  • 31S. Abiteboul, F. G'sell.

    Les algorithmes pourraient-ils remplacer les juges ?, in: Le Big Data et le droit, Thèmes et Commentaire, Dalloz, 2019.

    https://hal.inria.fr/hal-02304016

Other Publications

References in notes
  • 33S. Abiteboul, B. André, D. Kaplan.

    Managing your digital life, in: Commun. ACM, 2015, vol. 58, no 5, pp. 32-35.

    http://doi.acm.org/10.1145/2670528
  • 34S. Abiteboul, P. Bourhis, V. Vianu.

    Comparing workflow specification languages: A matter of views, in: ACM Trans. Database Syst., 2012, vol. 37, no 2, pp. 10:1-10:59.

    http://doi.acm.org/10.1145/2188349.2188352
  • 35S. Abiteboul, P. Buneman, D. Suciu.

    Data on the Web: From Relations to Semistructured Data and XML, Morgan Kaufmann, 1999.
  • 36S. Abiteboul, L. Herr, J. Van den Bussche.

    Temporal Versus First-Order Logic to Query Temporal Databases, in: Proceedings of the Fifteenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, June 3-5, 1996, Montreal, Canada, R. Hull (editor), ACM Press, 1996, pp. 49-57.

    http://doi.acm.org/10.1145/237661.237674
  • 37S. Abiteboul, R. Hull, V. Vianu.

    Foundations of Databases, Addison-Wesley, 1995.

    http://webdam.inria.fr/Alice/
  • 38S. Abiteboul, I. Manolescu, P. Rigaux, M. Rousset, P. Senellart.

    Web Data Management, Cambridge University Press, 2011.

    http://webdam.inria.fr/Jorge
  • 39A. Amarilli, P. Bourhis, P. Senellart.

    Provenance Circuits for Trees and Treelike Instances, in: Automata, Languages, and Programming - 42nd International Colloquium, ICALP 2015, Kyoto, Japan, July 6-10, 2015, Proceedings, Part II, 2015, pp. 56-68.

    https://doi.org/10.1007/978-3-662-47666-6_5
  • 40A. Amarilli, P. Bourhis, P. Senellart.

    Tractable Lineages on Treelike Instances: Limits and Extensions, in: Proceedings of the 35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, PODS 2016, San Francisco, CA, USA, June 26 - July 01, 2016, T. Milo, W. Tan (editors), ACM, 2016, pp. 355-370.

    http://doi.acm.org/10.1145/2902251.2902301
  • 41Y. Amsterdamer, Y. Grossman, T. Milo, P. Senellart.

    CrowdMiner: Mining association rules from the crowd, in: PVLDB, 2013, vol. 6, no 12, pp. 1250-1253.

    http://www.vldb.org/pvldb/vol6/p1250-amsterdamer.pdf
  • 42P. B. Baeza.

    Querying graph databases, in: Proceedings of the 32nd ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, PODS 2013, New York, NY, USA - June 22 - 27, 2013, R. Hull, W. Fan (editors), ACM, 2013, pp. 175-188.

    http://doi.acm.org/10.1145/2463664.2465216
  • 43D. Barbará, H. Garcia-Molina, D. Porter.

    The Management of Probabilistic Data, in: IEEE Trans. Knowl. Data Eng., 1992, vol. 4, no 5, pp. 487-502.

    https://doi.org/10.1109/69.166990
  • 44D. Basu, Q. Lin, W. Chen, H. T. Vo, Z. Yuan, P. Senellart, S. Bressan.

    Regularized Cost-Model Oblivious Database Tuning with Reinforcement Learning, in: T. Large-Scale Data- and Knowledge-Centered Systems, 2016, vol. 28, pp. 96-132.

    https://doi.org/10.1007/978-3-662-53455-7_5
  • 45M. Benedikt, G. Gottlob, P. Senellart.

    Determining relevance of accesses at runtime, in: Proceedings of the 30th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, PODS 2011, June 12-16, 2011, Athens, Greece, M. Lenzerini, T. Schwentick (editors), ACM, 2011, pp. 211-222.

    http://doi.acm.org/10.1145/1989284.1989309
  • 46M. Benedikt, P. Senellart.

    Databases, in: Computer Science, The Hardware, Software and Heart of It, Springer, 2011, pp. 169-229.

    https://doi.org/10.1007/978-1-4614-1168-0_10
  • 47M. Bienvenu, D. Deutch, D. Martinenghi, P. Senellart, F. M. Suchanek.

    Dealing with the Deep Web and all its Quirks, in: Proceedings of the Second International Workshop on Searching and Integrating New Web Data Sources, Istanbul, Turkey, August 31, 2012, M. Brambilla, S. Ceri, T. Furche, G. Gottlob (editors), CEUR Workshop Proceedings, CEUR-WS.org, 2012, vol. 884, pp. 21-24.

    http://ceur-ws.org/Vol-884/VLDS2012_p21_Bienvenu.pdf
  • 48M. Bojańczyk, L. Segoufin, S. Toruńczyk.

    Verification of database-driven systems via amalgamation, in: Proceedings of the 32nd ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, PODS 2013, New York, NY, USA - June 22 - 27, 2013, R. Hull, W. Fan (editors), ACM, 2013, pp. 63-74.

    http://doi.acm.org/10.1145/2463664.2465228
  • 49P. Buneman, S. Khanna, W.-C. Tan.

    Why and Where: A Characterization of Data Provenance, in: Database Theory - ICDT 2001, 8th International Conference, London, UK, January 4-6, 2001, Proceedings., J. Van den Bussche, V. Vianu (editors), Lecture Notes in Computer Science, Springer, 2001, vol. 1973, pp. 316-330.

    https://doi.org/10.1007/3-540-44503-X_20
  • 50B. Courcelle.

    The Monadic Second-Order Logic of Graphs. I. Recognizable Sets of Finite Graphs, in: Inf. Comput., 1990, vol. 85, no 1, pp. 12-75.

    https://doi.org/10.1016/0890-5401(90)90043-H
  • 51N. N. Dalvi, D. Suciu.

    The dichotomy of probabilistic inference for unions of conjunctive queries, in: J. ACM, 2012, vol. 59, no 6, pp. 30:1-30:87.

    http://doi.acm.org/10.1145/2395116.2395119
  • 52A. Deshpande, Z. G. Ives, V. Raman.

    Adaptive Query Processing, in: Foundations and Trends in Databases, 2007, vol. 1, no 1, pp. 1-140.

    https://doi.org/10.1561/1900000001
  • 53P. Donmez, J. G. Carbonell.

    Proactive learning: cost-sensitive active learning with multiple imperfect oracles, in: Proceedings of the 17th ACM Conference on Information and Knowledge Management, CIKM 2008, Napa Valley, California, USA, October 26-30, 2008, J. G. Shanahan, S. Amer-Yahia, I. Manolescu, Y. Zhang, D. A. Evans, A. Kolcz, K. Choi, A. Chowdhury (editors), ACM, 2008, pp. 619-628.

    http://doi.acm.org/10.1145/1458082.1458165
  • 54M. Faheem, P. Senellart.

    Adaptive Web Crawling Through Structure-Based Link Classification, in: Digital Libraries: Providing Quality Information - 17th International Conference on Asia-Pacific Digital Libraries, ICADL 2015, Seoul, Korea, December 9-12, 2015, Proceedings, R. B. Allen, J. Hunter, M. L. Zeng (editors), Lecture Notes in Computer Science, Springer, 2015, vol. 9469, pp. 39-51.

    https://doi.org/10.1007/978-3-319-27974-9_5
  • 55L. Getoor.

    Introduction to statistical relational learning, MIT Press, 2007.
  • 56G. Gouriten, S. Maniu, P. Senellart.

    Scalable, generic, and adaptive systems for focused crawling, in: 25th ACM Conference on Hypertext and Social Media, HT '14, Santiago, Chile, September 1-4, 2014, L. Ferres, G. Rossi, V. A. F. Almeida, E. Herder (editors), ACM, 2014, pp. 35-45.

    http://doi.acm.org/10.1145/2631775.2631795
  • 57T. J. Green, G. Karvounarakis, V. Tannen.

    Provenance semirings, in: Proceedings of the Twenty-Sixth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, June 11-13, 2007, Beijing, China, L. Libkin (editor), ACM, 2007, pp. 31-40.

    http://doi.acm.org/10.1145/1265530.1265535
  • 58T. J. Green, V. Tannen.

    Models for Incomplete and Probabilistic Information, in: IEEE Data Eng. Bull., 2006, vol. 29, no 1, pp. 17-24.

    http://sites.computer.org/debull/A06mar/green.ps
  • 59A. Y. Halevy.

    Answering queries using views: A survey, in: VLDB J., 2001, vol. 10, no 4, pp. 270-294.

    https://doi.org/10.1007/s007780100054
  • 60M. A. Hearst, S. T. Dumais, E. Osuna, J. Platt, B. Scholkopf.

    Support vector machines, in: IEEE Intelligent Systems, 1998, vol. 13, no 4, pp. 18-28.

    https://doi.org/10.1109/5254.708428
  • 61T. Imielinski, W. Lipski Jr..

    Incomplete Information in Relational Databases, in: J. ACM, 1984, vol. 31, no 4, pp. 761-791.

    http://doi.acm.org/10.1145/1634.1886
  • 62B. Kimelfeld, P. Senellart.

    Probabilistic XML: Models and Complexity, in: Advances in Probabilistic Databases for Uncertain Information Management, Z. Ma, L. Yan (editors), Studies in Fuzziness and Soft Computing, Springer, 2013, vol. 304, pp. 39-66.

    https://doi.org/10.1007/978-3-642-37509-5_3
  • 63A. C. Klug.

    Equivalence of Relational Algebra and Relational Calculus Query Languages Having Aggregate Functions, in: J. ACM, 1982, vol. 29, no 3, pp. 699-717.

    http://doi.acm.org/10.1145/322326.322332
  • 64D. Kossmann.

    The State of the art in distributed query processing, in: ACM Comput. Surv., 2000, vol. 32, no 4, pp. 422-469.

    http://doi.acm.org/10.1145/371578.371598
  • 65J. D. Lafferty, A. McCallum, F. C. N. Pereira.

    Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data, in: Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28 - July 1, 2001, C. E. Brodley, A. P. Danyluk (editors), Morgan Kaufmann, 2001, pp. 282-289.
  • 66S. Lei, S. Maniu, L. Mo, R. Cheng, P. Senellart.

    Online Influence Maximization, in: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney, NSW, Australia, August 10-13, 2015, 2015, pp. 645-654.

    http://doi.acm.org/10.1145/2783258.2783271
  • 67F. Neven.

    Automata Theory for XML Researchers, in: SIGMOD Record, 2002, vol. 31, no 3, pp. 39-46.

    http://doi.acm.org/10.1145/601858.601869
  • 68P. Senellart, A. Mittal, D. Muschick, R. Gilleron, M. Tommasi.

    Automatic wrapper induction from hidden-web sources with domain knowledge, in: 10th ACM International Workshop on Web Information and Data Management (WIDM 2008), Napa Valley, California, USA, October 30, 2008, C. Y. Chan, N. Polyzotis (editors), ACM, 2008, pp. 9-16.

    http://doi.acm.org/10.1145/1458502.1458505
  • 69B. Settles, M. Craven, L. Friedland.

    Active learning with real annotation costs, in: NIPS 2008 Workshop on Cost-Sensitive Learning, 2008.

    http://burrsettles.com/pub/settles.nips08ws.pdf
  • 70B. Settles.

    Active Learning, Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers, 2012.

    https://doi.org/10.2200/S00429ED1V01Y201207AIM018
  • 71F. M. Suchanek, S. Abiteboul, P. Senellart.

    PARIS: Probabilistic Alignment of Relations, Instances, and Schema, in: PVLDB, 2011, vol. 5, no 3, pp. 157-168.

    http://www.vldb.org/pvldb/vol5/p157_fabianmsuchanek_vldb2012.pdf
  • 72D. Suciu, D. Olteanu, C. Ré, C. Koch.

    Probabilistic Databases, Synthesis Lectures on Data Management, Morgan & Claypool Publishers, 2011.

    https://doi.org/10.2200/S00362ED1V01Y201105DTM016
  • 73R. S. Sutton, A. G. Barto.

    Reinforcement learning - an introduction, Adaptive computation and machine learning, MIT Press, 1998.

    http://www.worldcat.org/oclc/37293240
  • 74M. Y. Vardi.

    The Complexity of Relational Query Languages (Extended Abstract), in: Proceedings of the 14th Annual ACM Symposium on Theory of Computing, May 5-7, 1982, San Francisco, California, USA, H. R. Lewis, B. B. Simons, W. A. Burkhard, L. H. Landweber (editors), ACM, 1982, pp. 137-146.

    http://doi.acm.org/10.1145/800070.802186
  • 75K. Zhou, M. Lalmas, T. Sakai, R. Cummins, J. M. Jose.

    On the reliability and intuitiveness of aggregated search metrics, in: 22nd ACM International Conference on Information and Knowledge Management, CIKM'13, San Francisco, CA, USA, October 27 - November 1, 2013, Q. He, A. Iyengar, W. Nejdl, J. Pei, R. Rastogi (editors), ACM, 2013, pp. 689-698.

    http://doi.acm.org/10.1145/2505515.2505691
  • 76M. T. Özsu, P. Valduriez.

    Principles of Distributed Database Systems, Third Edition, Springer, 2011.

    https://doi.org/10.1007/978-1-4419-8834-8


previous Previous | up Home