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Relational Concept Analysis in Practice: Capitalizing on Data Modeling Using Design Patterns

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Formal Concept Analysis (ICFCA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13934))

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Abstract

Many applications of Formal Concept Analysis (FCA) and its diverse extensions have been carried out in recent years. Among these extensions, Relational Concept Analysis (RCA) is one approach for addressing knowledge discovery in multi-relational datasets. Applying RCA requires stating a question of interest and encoding the dataset into the input RCA data model, i.e. an Entity-Relationship model with only Boolean attributes in the entity description and unidirectional binary relationships. From the various concrete RCA applications, recurring encoding patterns can be observed, that we aim to capitalize taking software engineering design patterns as a source of inspiration. This capitalization work intends to rationalize and facilitate encoding in future RCA applications. In this paper, we describe an approach for defining such design patterns, and we present two design patterns: “Separate/Gather Views” and “Level Relations”.

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Acknowledgements

This work was supported by the ANR SmartFCA project, Grant ANR-21-CE23-0023 of the French National Research Agency.

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Authors and Affiliations

  1. Université de Strasbourg, CNRS, ENGEES, ICube UMR 7537, 67000, Strasbourg, France

    Agnès Braud, Xavier Dolques & Florence Le Ber

  2. LIRMM, Univ. Montpellier, CNRS, Montpellier, France

    Marianne Huchard

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

    Pierre Martin

Authors
  1. Agnès Braud
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  2. Xavier Dolques
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  3. Marianne Huchard
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  4. Florence Le Ber
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  5. Pierre Martin
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Corresponding author

Correspondence to Marianne Huchard .

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Editors and Affiliations

  1. Universität Kassel, Kassel, Germany

    Dominik Dürrschnabel

  2. Universidad de Málaga, Málaga, Spain

    Domingo López Rodríguez

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Braud, A., Dolques, X., Huchard, M., Le Ber, F., Martin, P. (2023). Relational Concept Analysis in Practice: Capitalizing on Data Modeling Using Design Patterns. In: Dürrschnabel, D., López Rodríguez, D. (eds) Formal Concept Analysis. ICFCA 2023. Lecture Notes in Computer Science(), vol 13934. Springer, Cham. https://doi.org/10.1007/978-3-031-35949-1_12

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  • DOI: https://doi.org/10.1007/978-3-031-35949-1_12

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