On-demand Relational Concept Analysis

  • Alexandre Bazin
  • Jessie CarbonnelEmail author
  • Marianne Huchard
  • Giacomo Kahn
  • Priscilla Keip
  • Amirouche Ouzerdine
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11511)


Formal Concept Analysis (FCA) and its associated conceptual structures are used to support exploratory search through conceptual navigation. Relational Concept Analysis (RCA) is an extension of Formal Concept Analysis to process relational datasets. RCA and its multiple interconnected structures represent good candidates to support exploratory search in relational datasets, as they are enabling navigation within a structure as well as between the connected structures. However, building the entire structures does not present an efficient solution to explore a small localised area of the dataset, to retrieve the closest alternatives to a given query. In these cases, generating only a concept and its neighbour concepts at each navigation step appears as a less costly alternative. In this paper, we propose an algorithm to compute a concept, and its neighbourhood, in connected concept lattices. The concepts are generated directly from the relational context family, and possess both formal and relational attributes. The algorithm takes into account two RCA scaling operators and it is implemented in the RCAExplore tool.


Relational Concept Analysis Formal Concept Analysis Exploratory search On-demand generation Local generation 



The authors warmly thank Xavier Dolques who helped us during the implementation in RCAexplore. This work was supported by the INRA-CIRAD Glofoods metaprogramme (Knomana project) and by the French National Research Agency under the Investments for the Future Program, referred as ANR-16-CONV-0004.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Alexandre Bazin
    • 1
  • Jessie Carbonnel
    • 2
    Email author
  • Marianne Huchard
    • 2
  • Giacomo Kahn
    • 3
  • Priscilla Keip
    • 4
    • 5
  • Amirouche Ouzerdine
    • 2
  1. 1.Université de Lorraine, CNRS, Inria, LORIANancyFrance
  2. 2.LIRMM, CNRS and Université de MontpellierMontpellierFrance
  3. 3.Université d’Orléans, INSA Centre Val de Loire, LIFOOrléansFrance
  4. 4.CIRAD, UPR AIDAMontpellierFrance
  5. 5.AIDA, Univ Montpellier, CIRADMontpellierFrance

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