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On-demand Relational Concept Analysis

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Formal Concept Analysis (ICFCA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11511))

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Abstract

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.

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Notes

  1. 1.

    http://dataqual.engees.unistra.fr/.

  2. 2.

    http://www.cirad.fr/en/news/all-news-items/articles/2017/science/identifying-plants-used-as-natural-pesticides-in-africa-knomana.

  3. 3.

    http://dataqual.engees.unistra.fr/logiciels/rcaExplore.

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Acknowledgement

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.

Author information

Authors and Affiliations

  1. Université de Lorraine, CNRS, Inria, LORIA, F54000, Nancy, France

    Alexandre Bazin

  2. LIRMM, CNRS and Université de Montpellier, Montpellier, France

    Jessie Carbonnel, Marianne Huchard & Amirouche Ouzerdine

  3. Université d’Orléans, INSA Centre Val de Loire, LIFO, Orléans, France

    Giacomo Kahn

  4. CIRAD, UPR AIDA, 34398, Montpellier, France

    Priscilla Keip

  5. AIDA, Univ Montpellier, CIRAD, Montpellier, France

    Priscilla Keip

Authors
  1. Alexandre Bazin
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  2. Jessie Carbonnel
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  3. Marianne Huchard
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  4. Giacomo Kahn
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  5. Priscilla Keip
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  6. Amirouche Ouzerdine
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Corresponding author

Correspondence to Jessie Carbonnel .

Editor information

Editors and Affiliations

  1. Babeș-Bolyai University, Cluj-Napoca, Romania

    Diana Cristea

  2. University of Strasbourg, ENGEES, Strasbourg, France

    Florence Le Ber

  3. Frankfurt University of Applied Sciences, Frankfurt, Germany

    Baris Sertkaya

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Bazin, A., Carbonnel, J., Huchard, M., Kahn, G., Keip, P., Ouzerdine, A. (2019). On-demand Relational Concept Analysis. In: Cristea, D., Le Ber, F., Sertkaya, B. (eds) Formal Concept Analysis. ICFCA 2019. Lecture Notes in Computer Science(), vol 11511. Springer, Cham. https://doi.org/10.1007/978-3-030-21462-3_11

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  • DOI: https://doi.org/10.1007/978-3-030-21462-3_11

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  • Online ISBN: 978-3-030-21462-3

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