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Computer Science

D-Index
38
Citations
5115
World Ranking
10365
National Ranking
252

Overview

Jean-François Boulicaut is affiliated with the Institut National des Sciences Appliquées de Lyon in France. Their research is situated primarily within the fields of Computer Science and Agricultural and Biological Sciences.

Their work spans various specialized subfields including Information Systems, Artificial Intelligence, Computational Theory and Mathematics, Plant Science, and Signal Processing. The key topics addressed in their publications cover Data Mining Algorithms and Applications, Rough Sets and Fuzzy Logic, Data Management and Algorithms, Artificial Intelligence in Games, Metaheuristic Optimization Algorithms Research, Video Analysis and Summarization, and Gambling Behavior and Treatments.

Jean-François Boulicaut has published multiple papers in prominent venues with a focus on knowledge and information systems as well as applications in gaming and pattern mining. Notable recent papers include:

  • A Behavioral Pattern Mining Approach to Model Player Skills in Rocket League, 2020, 2020 IEEE Conference on Games (CoG)
  • Anytime mining of sequential discriminative patterns in labeled sequences, 2020, Knowledge and Information Systems
  • Mining evolutions of complex spatial objects using a single-attributed Directed Acyclic Graph, 2020, Knowledge and Information Systems

Their frequent co-authors include Alexandre Millot, Rémy Cazabet, Romain Mathonat, Mehdi Kaytoue, and Diana Nurbakova, indicating collaborative research efforts in areas related to data mining and artificial intelligence.

Jean-François Boulicaut's publications are often found in the journals and conferences such as Knowledge and Information Systems and the IEEE Conference on Games, reflecting an interdisciplinary approach that combines theoretical foundations with practical applications.

Best Publications

  • Free-Sets: A Condensed Representation of Boolean Data for the Approximation of Frequency Queries

    Jean-François Boulicaut;Artur Bykowski;Christophe Rigotti

  • Machine Learning, ECML 2004

    Jean-François Boulicaut;Floriana Esposito;Fosca Giannotti;Dino Pedreschi

  • Strong-association-rule mining for large-scale gene-expression data analysis: a case study on human SAGE data

    Céline Becquet;Sylvain Blachon;Baptiste Jeudy;Jean-Francois Boulicaut

  • Knowledge Discovery in Databases: PKDD 2004

    Jean-François Boulicaut;Floriana Esposito;Fosca Giannotti;Dino Pedreschi

  • Approximation of Frequency Queris by Means of Free-Sets

    Jean-Francois Boulicaut;Artur Bykowski;Christophe Rigotti

  • A survey on condensed representations for frequent sets

    Toon Calders;Christophe Rigotti;Jean-François Boulicaut

  • Closed patterns meet n-ary relations

    Loïc Cerf;Jérémy Besson;Céline Robardet;Jean-François Boulicaut

  • Using Queries to Improve Database Reverse Engineering

    Jean-Marc Petit;Jacques Kouloumdjian;Jean-Francois Boulicaut;Farouk Toumani

  • Frequent Closures as a Concise Representation for Binary Data Mining

    Jean-Francois Boulicaut;Artur Bykowski

  • Constraint-based concept mining and its application to microarray data analysis

    Jérémy Besson;Céline Robardet;Jean-François Boulicaut;Sophie Rome

  • Towards the reverse engineering of renormalized relational databases

    J.-M. Petit;F. Toumani;J.-F. Boulicaut;J. Kouloumdjian

  • Constraint-based Data Mining

    Jean-François Boulicaut;Baptiste Jeudy

  • Constraint-based mining and inductive databases

    Jean-François Boulicaut;Luc de Raedt;Heikki Mannila

  • Modeling KDD Processes within the Inductive Database Framework

    Jean-Francois Boulicaut;Mika Klemettinen;Heikki Mannila

  • Data-Peeler: Constraint-Based Closed Pattern Mining in n-ary Relations

    Loïc Cerf;Jérémy Besson;Céline Robardet;Jean-François Boulicaut

  • Constrained Co-clustering of Gene Expression Data

    Ruggero G. Pensa;Jean-François Boulicaut

  • Mining Graph Topological Patterns: Finding Covariations among Vertex Descriptors

    Unknown

  • Mining a new fault-tolerant pattern type as an alternative to formal concept discovery

    Jérémy Besson;Céline Robardet;Jean-François Boulicaut

  • Assessment of discretization techniques for relevant pattern discovery from gene expression data

    Ruggero G. Pensa;Claire Leschi;Jérémy Besson;Jean-François Boulicaut

  • Using transposition for pattern discovery from microarray data

    François Rioult;Jean-François Boulicaut;Bruno Crémilleux;Jérémy Besson

  • Data Peeler: Contraint-Based Closed Pattern Mining in n-ary Relations.

    Loïc Cerf;Jérémy Besson;Céline Robardet;Jean-François Boulicaut

  • Knowledge discovery in inductive databases : 4th International Workshop, KDID 2005, Porto, Portugal, October 3, 2005 : revised selected and invited papers

    Kdid;Francesco Bonchi;Jean-François Boulicaut

Frequent Co-Authors

Heikki Mannila
Heikki Mannila Aalto University
Floriana Esposito
Floriana Esposito University of Bari Aldo Moro
Dino Pedreschi
Dino Pedreschi University of Pisa
Luc De Raedt
Luc De Raedt KU Leuven
Francesco Bonchi
Francesco Bonchi Institute for Scientific Interchange
Michael R. Berthold
Michael R. Berthold University of Konstanz
Moustafa Bensafi
Moustafa Bensafi Grenoble Alpes University
Fosca Giannotti
Fosca Giannotti Scuola Normale Superiore di Pisa
Toon Calders
Toon Calders University of Antwerp
Yvan Rahbé
Yvan Rahbé Institut National des Sciences Appliquées de Lyon

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