Number of documents

8

Thomas Guyet


Research interests

My research area is artificial intelligence (AI) with a multidisciplinary approach - algorithmic, design methodologies and cognitive science. I am particularly interested in discovering spatial and temporal patterns in semantically rich datasets. My areas of application are related to agronomy (mainly landscapes) and health (care pathways analysis).

My first research direction is the temporal and spatial pattern mining. Data from the observation of living systems (agricultural and medical systems) have a strong spatial or temporal dimension. But the spatial and temporal information is often underutilized in the data mining algorithms. The challenge lies in identifying new kind of temporal/spatial patterns that have valuable properties to make possible their extraction by complete and correct algorithms. A recent approach I'm developping is the use declarative programming, more especially Answer Set Programming (ASP) with clingo, to mix pattern mining and reasonning.
My second research direction aims at better including the user in the loop of knowledge discovery. Specifically, I am interested in implementing interactive systems to support users in their exploration process of large datasets. To acheive this goal I propose an enactive point of view of the data interpretation that brings creative solutions to take into account the cognitive ergonomy of the knowledge discovery tools.


"Catherine Garbay"   

Journal articles2 documents

  • Thomas Guyet, Catherine Garbay, Michel Dojat. Knowledge construction from time series data using a collaborative exploration approach. Journal of Biomedical Informatics, Elsevier, 2007, 40 (6), pp.672-687. ⟨10.1016/j.jbi.2007.09.006⟩. ⟨inria-00461373⟩
  • Thomas Guyet, Catherine Garbay, Michel Dojat. Knowledge construction from time series data using a collaborative exploration system.. Journal of Biomedical Informatics, Elsevier, 2007, 40 (6), pp.672-87. ⟨10.1016/j.jbi.2007.09.006⟩. ⟨inserm-00381739⟩

Conference papers5 documents

  • Thomas Guyet, Catherine Garbay, Michel Dojat. Interprétation collaborative de séries temporelles. Colloque de l'association pour la recherche cognitive, Dec 2009, Rouen, France. ⟨inria-00461366⟩
  • Thomas Guyet, Catherine Garbay, Dojat Michel. A human-machine cooperative approach for time series data interpretation. 11th Conference on Artificial Intelligence in Medicine (AIME 2007), Jul 2007, Amsterdam, Netherlands. pp.3-12. ⟨inserm-00519815⟩
  • Thomas Guyet, Catherine Garbay, Michel Dojat. A Human-Machine Cooperative Approach for Time Series Data Interpretation. The 11th Conference on Artificial Intelligence In Medicine, Aug 2007, Aberdeen, United Kingdom. ⟨10.1007/978-3-540-73599-1_1⟩. ⟨inria-00461454⟩
  • Thomas Guyet, Catherine Garbay, Michel Dojat. Computer/Human Structural Coupling for Data Interpretation. Proc ENACTIVE 2006: Third International Conference on Enactive Interfaces, Enaction and Complexity, 2006, Montpellier, France. ⟨hal-00953904⟩
  • Thomas Guyet, Catherine Garbay, Michel Dojat. Human-Computer interaction to learn scenarios from ICU multivariate time series. Artificial Intelligence in Medicine. Proceedings of the European Conference on Artificial Intelligence in Medicine AIME'05, Jul 2005, Aberdeen- Scotland, United Kingdom. pp.424-428. ⟨inserm-00519870⟩

Other publications1 document

  • Thomas Guyet, Catherine Garbay, Michel Dojat. Algorithme d'Apprentissage de Scénarios à partir de Séries Symboliques Temporelles. 2006. ⟨hal-00954115⟩