Number of documents


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.

Véronique Masson   

Conference papers4 documents

  • Philippe Besnard, Thomas Guyet, Véronique Masson. Admissible generalizations of examples as rules . 11e Journées d'Intelligence Artificielle Fondamentale, Jul 2017, Caen, France. ⟨hal-01576047⟩
  • Thomas Guyet, René Quiniou, Véronique Masson. Mining relevant interval rules. International Conference on Formal Concept Analysis, Jun 2017, Rennes, France. ⟨hal-01584981⟩
  • Kiril Gashteovski, Thomas Guyet, René Quiniou, Alzennyr da Silva, Véronique Masson. Sequential pattern mining for customer relationship management analysis. Atelier GAST@EGC2015, Jan 2015, Luxembourg, Luxembourg. ⟨hal-01097466⟩
  • Marie-Odile Cordier, Thomas Guyet, Christine Largouët, Véronique Masson, Henri-Maxime Suchier. Apprentissage incrémental de règles de décision à partir de données d'un simulateur. Atelier INFORSID : Systèmes d'Information et de Décision pour l'Environnement, 2009, Toulouse, France. ⟨inria-00460719⟩

Documents associated with scientific events1 document

  • Philippe Besnard, Thomas Guyet, Véronique Masson. Admissible Generalizations of Examples as Rules. One-day Workshop on Machine Learning and Explainability 2018, Oct 2018, Orléans, France. pp.1-29. ⟨hal-01940129⟩