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Interestingness Measures for Exploratory Data Analysis: a Survey

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New Trends in Database and Information Systems (ADBIS 2024)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2186))

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Abstract

Exploratory Data Analysis (EDA) is the tedious activity of interactively analyzing a dataset to extract insights. Many approaches aiming at supporting EDA were recently proposed. They all rely on interestingness measures to score the importance of insights. This paper surveys and categorizes the different interestingness measures proposed in the literature for approaches aiming at automating EDA. The lessons learned from this survey allow to point out promising research directions.

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Notes

  1. 1.

    [13] proposes peculiarity, surprise, diversity and presentation (some of them with different names) and [15, 20] propose relevance, novelty, peculiarity and surprise.

  2. 2.

    Called surprise in [12], but reclassified here since it does not refer to a user’s belief.

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Author information

Authors and Affiliations

  1. LIFAT - University of Tours, Blois, France

    Alexandre Chanson, Nicolas Labroche & Verónika Perlata

  2. LIFO - University of Orléans, Orléans, France

    Patrick Marcel

  3. University of Ioannina, Ioannina, Greece

    Panos Vassiliadis

Authors
  1. Alexandre Chanson
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  2. Nicolas Labroche
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  3. Patrick Marcel
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  4. Verónika Perlata
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  5. Panos Vassiliadis
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Corresponding author

Correspondence to Patrick Marcel .

Editor information

Editors and Affiliations

  1. Lebanese American University, Beirut, Lebanon

    Joe Tekli

  2. Free University of Bozen-Bolzano, Bolzano, Italy

    Johann Gamper

  3. Univ Pau & Pays de l'Adour, Anglet, Anglet, France

    Richard Chbeir

  4. Open University of Cyprus, Nicosia, Cyprus

    Yannis Manolopoulos

  5. Univ Pau & Pays de l'Adour, Anglet, Anglet, France

    Salma Sassi

  6. University of Novi Sad, Novi Sad, Serbia

    Mirjana Ivanovic

  7. Délégation Rhône Auvergne, Villeurbanne, France

    Genoveva Vargas-Solar

  8. University of Calabria, Arcavacata, Italy

    Ester Zumpano

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Chanson, A., Labroche, N., Marcel, P., Perlata, V., Vassiliadis, P. (2025). Interestingness Measures for Exploratory Data Analysis: a Survey. In: Tekli, J., et al. New Trends in Database and Information Systems. ADBIS 2024. Communications in Computer and Information Science, vol 2186. Springer, Cham. https://doi.org/10.1007/978-3-031-70421-5_2

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  • DOI: https://doi.org/10.1007/978-3-031-70421-5_2

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  • Print ISBN: 978-3-031-70420-8

  • Online ISBN: 978-3-031-70421-5

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