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.

"Yves Moinard"   

Journal articles1 document

  • Thomas Guyet, Yves Moinard, René Quiniou. Programmation par ensembles réponses pour simuler l’assolement d’un paysage. Revue des Sciences et Technologies de l'Information - Série RIA : Revue d'Intelligence Artificielle, Lavoisier, 2015, Numéro spécial RFIA 2014, 29 (3-4), pp.28. ⟨hal-01184092⟩

Conference papers4 documents

  • Thomas Guyet, Yves Moinard, Jacques Nicolas, René Quiniou. Packing graphs with ASP for landscape simulation. IJCAI 2016 - 25th International joint conference on artificial intelligence , Jul 2016, New-york, United States. pp.8. ⟨hal-01327368⟩
  • Thomas Guyet, Yves Moinard, René Quiniou, Torsten Schaub. Fouille de motifs séquentiels avec ASP. Extraction et Gestion de Connaissances (EGC), 2016, Reims, France. ⟨hal-01239501⟩
  • Thomas Guyet, Yves Moinard, René Quiniou. Using Answer Set Programming for pattern mining. Intelligence Artificielle Fondamentale, Jun 2014, Angers, France. ⟨hal-01069092⟩
  • Thomas Guyet, Yves Moinard. Programmation par ensembles réponses pour simuler l'assolement d'un paysage. Reconnaissance de Formes et Intelligence Artificielle (RFIA) 2014, Jun 2014, France. ⟨hal-00989199⟩

Book sections1 document

  • Thomas Guyet, Yves Moinard, René Quiniou, Torsten Schaub. Efficiency Analysis of ASP Encodings for Sequential Pattern Mining Tasks. Bruno Pinaud; Fabrice Guillet; Bruno Cremilleux; Cyril de Runz. Advances in Knowledge Discovery and Management, 7, Springer, pp.41--81, 2017, 978-3-319-65405-8. ⟨hal-01631879⟩