Bibliography

Major publications by the team in recent years

1P. Besnard, M.-O. Cordier, Y. Moinard.

Ontology-based inference for causal explanation, in: Integrated Computer-Aided Engineering, 2008, vol. 15, n^o 4, p. 351-367.

http://hal.inria.fr/inria-00476906/en/
2C. Gascuel Odoux, P. Aurousseau, M.-O. Cordier, P. Durand, F. Garcia, V. Masson, J. Salmon-Monviola, F. Tortrat, R. Trépos.

A decision-oriented model to evaluate the effect of land use and agricultural management on herbicide contamination in stream water, in: Environmental modelling & software, 2009, vol. 24, p. 1433-1446.

http://hal.inria.fr/hal-00544122/en
3Y. Pencolé, M.-O. Cordier.

A formal framework for the decentralised diagnosis of large scale discrete event systems and its application to telecommunication networks, in: Artificial Intelligence Journal, 2005, vol. 164, n^o 1-2, p. 121-170.

http://hal.inria.fr/inria-00511104/en/

Publications of the year

Articles in International Peer-Reviewed Journal

4C. Largouët, M.-O. Cordier, Y.-M. Le Bozec, Y. Zhao, G. Fontenelle.

Use Of Timed Automata And Model-Checking To Explore Scenarios On Ecosystem Models, in: Environmental Modelling and Software, November 2011. [ DOI : 10.1016/j.envsoft.2011.08.005 ]

http://hal.inria.fr/hal-00649275/en/
5J. Salmon-Monviola, C. Gascuel-Odoux, F. Garcia, F. Tortrat, M.-O. Cordier, V. Masson, R. Trépos.

Simulating the effect of techniques and environmental constraints on the spatio-temporal distribution of herbicide applications and stream losses, in: Agriculture, Ecosystems and Environment, January 2011, vol. 140, p. 382-394.

http://hal.inria.fr/hal-00618448/en
6K. Sedki, V. Delcroix.

A Model based on Influence Diagrams for Multi-Criteria Decision-Making, in: International Journal on Artificial Intelligence Tools (IJAIT), 2011.
7R. Trépos, A. Salleb-Aouissi, M.-O. Cordier, V. Masson, C. Gascuel-Odoux.

Building Actions From Classification Rules, in: Knowledge and Information Systems (KAIS) journal, June 2011.

http://hal.inria.fr/hal-00649388/en/

International Conferences with Proceedings

8T. Guyet, R. Quiniou.

Extracting temporal patterns from interval-based sequences, in: International Joint Conference on Artificial Intelligence (IJCAI), Barcelone, Spain, July 2011.

http://hal.inria.fr/inria-00618444/en

National Conferences with Proceeding

9T. Guyet, H. Nicolas, A. Diouck.

Segmentation multi-échelle de séries temporelles d'images satellite : Application à l'étude d'une période de sécheresse au Sénégal., in: Reconnaissance de Forme et Intelligence Artificielle (RFIA), Lyon, France, January 2012.

http://hal.inria.fr/hal-00646158/en
10T. Guyet, R. Quiniou.

Extraction de motifs temporels à partir de séquences d'événements avec intervalles temporels, in: Extraction et Gestion de Connaissances, Brest, France, January 2011.

http://hal.inria.fr/inria-00547629/en
11T. Guyet, R. Quiniou.

Extraction incrémentale de séquences fréquentes dans un flux d'itemsets, in: Extraction et Gestion de Connaissances (EGC'2012), Bordeaux, France, B. Pinaud, G. Melançon, Y. Lechevallier (editors), RNTI, Hermann, February 2012.

http://hal.inria.fr/hal-00648893/en/
12Y. Moinard.

Utilisation de la programmation par ensembles réponses (Answer Set Programming) sur de ”petits” problèmes, in: Cinquièmes Journées de l'Intelligence Artificielle Fondamentale (JIAF), Lyon, France, L. Cholvy, et al. (editors), LIRIS, June 2011.

http://hal.inria.fr/inria-00619527/en
13Y. Moinard.

Utiliser la programmation par ensembles réponses pour de petits problèmes, in: Reconnaissance de Forme et Intelligence Artificielle (RFIA), Lyon, France, January 2012.
14Y. Zhao, M.-O. Cordier, C. Largouët.

Répondre aux questions "Que faire pour" par synthèse de contrôleur sur des automates temporisés - Application à la gestion de la pêche, in: Reconnaissance des Formes et Intelligence Artificielle (RFIA), Lyon, France, January 2012.

http://hal.inria.fr/hal-00649182/en/

References in notes

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16S. Dzeroski, N. Lavrač (editors)

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17W. Hamscher, L. Console, J. de Kleer (editors)

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18C. Aggarwal.

Data Streams: Models and Algorithms, Advances in Database Systems, Springer, 2007.
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23P. Besnard, M.-O. Cordier.

Inferring causal explanations, in: Symbolic and Quantitative Approaches to Reasoning and Uncertainty (ECSQARU'99), A. Hunter, S. Parsons (editors), Lecture Notes in Artificial Intelligence, Springer-Verlag, 1999, vol. 1638, p. 55-67.
24P. Besnard, M.-O. Cordier, Y. Moinard.

Configurations for Inference between Causal Statements, in: KSEM 2006 (First Int. Conf. on Knowledge Science, Engineering and Management), J. Lang, F. Lin, J. Wang (editors), LNAI, Springer, aug 2006, n^o 4092, p. 292–304.

http://www.irisa.fr/dream/dataFiles/moinard/causeksempub.pdf
25P. Besnard, M.-O. Cordier, Y. Moinard.

Ontology-based inference for causal explanation, in: KSEM07 (Second International Conference on Knowledge Science, Engineering and Management), Z. Zhang, J. Siekmann (editors), LNAI, Springer, nov 2007, n^o 4798, p. 153-164.

http://www.irisa.fr/dream/dataFiles/moinard/ksem07bcausesonto.pdf
26P. Besnard, M.-O. Cordier, Y. Moinard.

Deriving explanations from causal information, in: ECAI 2008 (18th European Conference on Artificial Intelligence), Patras, Greece, M. Ghallab, C. D. Spytopoulos, N. Fakotakis, N. Avouris (editors), IOS Press, jul 2008, p. 723–724.
27P. Besnard, M.-O. Cordier, Y. Moinard.

Ontology-based inference for causal explanation, in: Integrated Computer-Aided Engineering, 2008, vol. 15, n^o 4, p. 351-367.
28C. Biernacki, G. Celeux, G. Govaert, F. Langrognet.

Model-Based Cluster and Discriminant Analysis with the MIXMOD Software, in: Computational Statistics and Data Analysis, 2006, vol. 51, n^o 2, p. 587-600.
29A. Bochman.

A Causal Theory of Abduction, in: 7th Int. Symposium on Logical Formalizations of Common Sense Reasoning, S. McIlraith, P. Peppas, M. Thielscher (editors), 2005, p. 33–38.
30Y. Chi, S. Nijssen, R. R. Muntz, J. N. Kok.

Frequent Subtree Mining–An Overview, in: Fundamenta Informaticae, IOS Press, 2005, vol. 66, p. 161–198.
31M.-O. Cordier, Y. Pencolé, L. Travé-Massuyès, T. Vidal.

Characterizing and checking self-healibility, in: ECAI 2008 (18th European Conference on Artificial Intelligence), Patras, Greece, M. Ghallab, C. D. Spytopoulos, N. Fakotakis, N. Avouris (editors), IOS Press, 2008, p. 789–790.
32A. Cornuéjols, L. Miclet.

Apprentissage artificiel : concepts et algorithmes, Eyrolles, 2002.
33L. De Raedt.

A perspective on inductive databases, in: SIGKDD Explor. Newsl., 2002, vol. 4, n^o 2, p. 69–77.

http://doi.acm.org/10.1145/772862.772871
34C. Dousson.

Chronicle Recognition System, 1994.
35C. Dousson.

Suivi d'évolutions et reconnaissance de chroniques, Université Paul Sabatier de Toulouse, LAAS-CNRS, Toulouse, 1994.
36C. Dousson, T. V. Duong.

Discovering Chronicles with Numerical Time Constraints from Alarm Logs for Monitoring Dynamic Systems., in: IJCAI, T. Dean (editor), Morgan Kaufmann, 1999, p. 620-626.
37C. Dousson, P. Gaborit, M. Ghallab.

Situation recognition: representation and algorithms, in: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Chambéry, France, 1993, p. 166-172.
38S. Dzeroski, L. Todorovski.

Discovering dynamics: from inductive logic programming to machine discovery, in: Journal of Intelligent Information Systems, 1995, vol. 4, p. 89-108.
39J. Gao, B. Ding, W. Fan, J. Han, P. S. Yu.

Classifying Data Streams with Skewed Class Distributions and Concept Drifts, in: IEEE Internet Computing, 2008, vol. 12, n^o 6, p. 37-49.
40M. Garofalakis, J. Gehrke, R. Rastogi.

Querying and Mining Data Streams: You Only Get One Look. Tutorial notes, in: ACM Int. Conf. on Management of Data, 2002.
41E. Giunchiglia, J. Lee, V. Lifschitz, N. McCain, H. Turner.

Nonmonotonic causal theories, in: Artificial Intelligence Journal, March 2004, vol. 153, n^o 1–2, p. 49–104.
42T. Guyet, R. Quiniou.

Mining temporal patterns with quantitative intervals, in: 4th International Workshop on Mining Complex Data at ICDM 2008, December 2008.
43D. T. Hau, E. W. Coiera.

Learning qualitative models of dynamic systems, in: Machine Learning, 1997, vol. 26, p. 177-211.
44T. Imielinski, H. Mannila.

A database perspective on knowledge discovery, in: Comm. of The ACM, 1996, vol. 39, p. 58–64.

http://courses.cs.ut.ee/datamining/2003/dm-seminar-fall/uploads/Main/arm-1.pdf
45M. Kubat, J. Gama, P. E. Utgoff.

Incremental learning and concept drift, in: Intell. Data Anal., 2004, vol. 8, n^o 3.
46X. Le Guillou, M.-O. Cordier, S. Robin, L. Rozé.

Chronicles for On-line Diagnosis of Distributed Systems, IRISA, Rennes, France, may 2008, n^o 1890.
47X. Le Guillou, M.-O. Cordier, S. Robin, L. Rozé.

Chronicles for On-line Diagnosis of Distributed Systems, in: ECAI'08 (18th European Conference on Artificial Intelligence), Patras, Greece, M. Ghallab, C. D. Spytopoulos, N. Fakotakis, N. Avouris (editors), IOS Press, july 2008.
48X. Le Guillou.

Chronicles for On-line Diagnosis of Distributed Systems, in: CAISE-dc'08 (Conference on Advanced Information Systems Engineering - doctoral consortium), Montpellier, France, june 2008.
49S. D. Lee, L. De Raedt.

Constraint Based Mining of First Order Sequences in SeqLog, LNCS, Springer-Verlag, 2004, vol. 2682, p. 154-173.
50H. Mannila, H. Toivonen, A. I. Verkamo.

Discovery of Frequent Episodes in Event Sequences, in: Data Mining and Knowledge Discovery, 1997, vol. 1, n^o 3, p. 259–289.
51A. Marascu, F. Masseglia.

Mining sequential patterns from data streams: a centroid approach, in: J. Intell. Inf. Syst., 2006, vol. 27, n^o 3, p. 291–307.

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52F. Masseglia, F. Cathala, P. Poncelet.

The PSP Approach for Mining Sequential Patterns, in: Proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery, 1998, p. 176–184.
53Y. Moinard.

A formalism for causal explanations with an Answer Set Programming translation, in: 4th International Conference on Knowledge Science, Engineering & Management (KSEM 2010), United Kingdom Belfast, B. Scotney, Z. Jin (editors), LNCS, Springer-Verlag, Aug 2010.

http://hal.inria.fr/inria-00511093/en
54Y. Moinard.

Using ASP with recent extensions for causal explanations, in: ASPOCP10, Answer Set Programming and Other Computing Paradigms Workshop, associated with ICLP, United Kingdom Edinburgh, M. Balduccini, S. Woltran (editors), Jul 2010.

http://hal.inria.fr/inria-00542880/en
55D. Page.

ILP: Just Do It, in: Proceedings of ILP'2000, J. Cussens, A. Frisch (editors), LNAI, Springer, 2000, vol. 1866, p. 3-18.
56Y. Pencolé, M.-O. Cordier, L. Rozé.

Incremental decentralized diagnosis approach for the supervision of a telecommunication network, in: DX'01 (International Workshop on Principles of Diagnosis), Sansicario, Italy, 2001.

http://www.irisa.fr/dream/dataFiles/ypencole/DX01.pdf
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http://www.irisa.fr/dream/dataFiles/quiniou/ilp01.pdf
58N. Ramaux, M. Dojat, D. Fontaine.

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59R. Reiter.

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66J. de Kleer, A. Mackworth, R. Reiter.

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