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Fuzzy Aggregators in Practice: Meta-Model and Implementation

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18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) (SOCO 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 749))

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Abstract

The J-CO Framework is a tool designed to provide analysts and data engineers with the capability to perform complex transformations on JSON databases through its query language, named \(J\text {-}CO\text {-}QL^{+}\).

Fuzzy aggregators are a powerful tool for decision making, when there is the need to combine together the evaluations of a group of experts to form a generalized opinion. Since soft querying can support decision making, it is straightforward to consider the introduction of the concept of fuzzy aggregation into \(J\text {-}CO\text {-}QL^{+}\).

This paper proposes a generic meta-model to define fuzzy aggregators, and novel \(J\text {-}CO\text {-}QL^{+}\) constructs to define user-defined fuzzy aggregators and use them in practice. A plausible case study shows that the meta-model can be effectively implemented within a stand-alone query language (\(J\text {-}CO\text {-}QL^{+}\)) that is supported by a tool (the J-CO Framework) that is available for the community.

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Notes

  1. 1.

    Github repository of the J-CO Framework: https://github.com/JcoProjectTeam/JcoProjectPage.

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Author information

Authors and Affiliations

  1. University of Bergamo, Viale Marconi 5, 24044, Dalmine, BG, Italy

    Paolo Fosci & Giuseppe Psaila

Authors
  1. Paolo Fosci
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  2. Giuseppe Psaila
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Corresponding author

Correspondence to Giuseppe Psaila .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Deusto, Bilbao, Spain

    Pablo García Bringas

  2. School of Industrial, Computer, University of Leon, León, Spain

    Hilde Pérez García

  3. Department of Mechanical Engineering, University of La Rioja, Logroño, Spain

    Francisco Javier Martínez de Pisón

  4. Data Science and Big Data Lab, Pablo de Olavide University, Seville, Spain

    Francisco Martínez Álvarez

  5. Data Science and Big Data Lab, Pablo de Olavide University, Seville, Spain

    Alicia Troncoso Lora

  6. Applied Computational Intelligence, University of Burgos, Burgos, Spain

    Álvaro Herrero

  7. Department of Industrial Engineering, University of A Coruña, A Coruña, Spain

    José Luis Calvo Rolle

  8. Department of Industrial Engineering, University of A Coruña, A Coruña, Spain

    Héctor Quintián

  9. Faculty of Science, University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Fosci, P., Psaila, G. (2023). Fuzzy Aggregators in Practice: Meta-Model and Implementation. In: García Bringas, P., et al. 18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023). SOCO 2023. Lecture Notes in Networks and Systems, vol 749. Springer, Cham. https://doi.org/10.1007/978-3-031-42529-5_6

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