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Thomas Guyet
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Documents
Identifiants chercheurs
- thomas-guyet
- 0000-0002-4909-5843
- Google Scholar : https://scholar.google.com/citations?user=cuNKrFoAAAAJ
- IdRef : 171949307
Présentation
Research interests
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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)](https://www.cs.utexas.edu/users/vl/papers/wiasp.pdf)** with [clingo](https://potassco.org), 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.
Publications
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Knowledge construction from time series data using a collaborative exploration system.Journal of Biomedical Informatics, 2007, 40 (6), pp.672-87. ⟨10.1016/j.jbi.2007.09.006⟩
Article dans une revue
inserm-00381739v1
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Knowledge construction from time series data using a collaborative exploration approachJournal of Biomedical Informatics, 2007, 40 (6), pp.672-687. ⟨10.1016/j.jbi.2007.09.006⟩
Article dans une revue
inria-00461373v1
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Interprétation collaborative de séries temporellesColloque de l'association pour la recherche cognitive, Dec 2009, Rouen, France
Communication dans un congrès
inria-00461366v1
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A human-machine cooperative approach for time series data interpretation11th Conference on Artificial Intelligence in Medicine (AIME 2007), Jul 2007, Amsterdam, Netherlands. pp.3-12
Communication dans un congrès
inserm-00519815v1
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A Human-Machine Cooperative Approach for Time Series Data InterpretationThe 11th Conference on Artificial Intelligence In Medicine, Aug 2007, Aberdeen, United Kingdom. ⟨10.1007/978-3-540-73599-1_1⟩
Communication dans un congrès
inria-00461454v1
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Human-Computer interaction to learn scenarios from ICU multivariate time seriesArtificial Intelligence in Medicine. Proceedings of the European Conference on Artificial Intelligence in Medicine AIME'05, Jul 2005, Aberdeen- Scotland, United Kingdom. pp.424-428
Communication dans un congrès
inserm-00519870v1
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