Supervision : Jean-Gabriel GANASCIA

Co-supervision : MATTIOLI Juliette

Introducing semantic knowledge in high level information fusion

A major stake of future decision support systems is to automate the processing of pieces of information coming from different sources in order to ease their understanding. The aim of our work is to recognize specific predefined situations from the observations gathered on different sources. Within the global information fusion process for situation recognition, we focus on three steps. First, the situations that must be recognized are represented using the conceptual graphs formalism. Using conceptual graphs allow us to take advantage of the theoretical studies that were achieved on this model. Then, compatible observation identification allows checking whether two observations relate to the same situation before any attempt to fuse them. The identification step relies on the use of domain adaptable similarity measures between conceptual graphs.Finally, the information fusion process proposed relies on the use of the maximal join operation on conceptual graphs. In order to fuse observations that are not exactly identical, we introduce domain knowledge inside the maximal join operation and relax the constraint of strict equality between the values of the concepts nodes of the graphs The validation of our work emphasizes on two aspects. First, we validate the validity of our approach and the usefulness of introducing domain knowledge inside the fusion process. To do so, the fusion platform developed during this thesis was used within a TV program recommendation system. Then, we validated the genericity of our approach and the adaptability of the fusion platform to new application domains by using the fusion platform within four other case studies.

2007-2021 Publications

• 2021
  • A. Faci, M.‑J. Lesot, C. Laudy : “Fuzzy Conceptual Graphs: a comparative discussion”, IEEE Symposium Series on Computational Intelligence, Foundations of Computational Intelligence (IEEE SSCI-FOCI 2021), Orlando, Florida, United States (2021)
  • A. Faci, M.‑J. Lesot, C. Laudy : “CG2A: Conceptual Graphs Generation Algorithm”, Joint Proceedings of the 19^th World Congress of the International Fuzzy Systems Association (IFSA), the 12^th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11^th International Summer School on Aggregation Operators (AGOP), Bratislava, Slovakia, pp. 63-70, (Atlantis Press) (2021)
  • A. Faci, M.‑J. Lesot, C. Laudy : “cgSpan: Pattern Mining in Conceptual Graphs”, Int. Conf. on Artificial Intelligence and Soft Computing (ICAISC2021), vol. 12855, Lecture Notes in Computer Science, Zakopane, Poland, pp. 149-158, (Springer) (2021)
• 2010
  • C. Fraboulet‑Laudy : “Fusion multi-sources d’informations de haut niveau : Introduction de connaissances sémantiques pour la gestion des incohérences”, thesis, phd defence 06/04/2010, supervision Ganascia, Jean-Gabriel, co-supervision : Mattioli, Juliette (2010)
• 2009
  • C. Laudy, J.‑G. Ganascia : “Introducing Semantic Knowledge in High-Level Fusion”, Proceedings of the SIMA workshop of Milcom2009, Boston, MA, United States, pp. 1-7, (IEEE) (2009)
  • C. Laudy, B. Habib, J.‑G. Ganascia : “Fusion of Claude Bernard’s Experiments for Scientific Discovery Reasoning”, 17^th International Conference on Conceptual Structures, ICCS 2009, vol. 5662, Lecture Notes in Computer Science, Moscow, Russian Federation, pp. 219-232, (Springer) (2009)
  • B. Habib, C. Laudy, J.‑G. Ganascia : “Using Fusion to Fill in the Gaps in Old Scientific Discoveries’ Notebooks”, IJCAI WORKSHOP ON GRAPH STRUCTURES FOR KNOWLEDGE REPRESENTATION AND REASONING (GKR 2009), Pasadena, California, United States (2009)
  • C. Laudy, J.‑G. Ganascia : “Using Maximal Join for Information Fusion”, FIRST IJCAI WORKSHOP ON GRAPH STRUCTURES FORKNOWLEDGE REPRESENTATION AND REASONING, Pasadena, California, United States (2009)
  • C. Laudy, J.‑G. Ganascia : “Fusion Symbolique pour la Recommandation de Programmes Televises”, EGC 2009, vol. RNTI-E-15, RNTI, Strasbourg, France, pp. 445-446 (2009)
• 2007
  • C. Laudy, J.‑G. Ganascia, C. Sedogbo : “High-level Fusion based on Conceptual Graphs”, 10^th International Conference on Information Fusion, Québec City, Québec, Canada, pp. 8-12, (IEEE) (2007)