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A Clustering Validation Index Based on Semantic Description

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Intelligent Systems (BRACIS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14197))

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Abstract

In clustering problems where the objective is not based on specifically spatial proximity, but rather on feature patterns and the semantic description, traditional internal cluster validation indices might not be appropriate. This article proposes a novel validity index to suggest the most appropriate number of clusters based on a semantic description of categorical databases. To assess our index, we also propose a synthetic data generator specifically designed for this type of application. We tested data sets with different configurations to assess the performance of the proposed index compared to well-known indices in the literature. Thus, we demonstrate that the index has great potential for discovering the number of clusters for the type of application studied and the data generator is able to produce relevant data sets for the internal validation process.

Supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES).

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Notes

  1. 1.

    https://dcta.mil.br/.

  2. 2.

    https://github.com/verri/sledge.

  3. 3.

    https://github.com/aquinordg/rdga_4k.

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Author information

Authors and Affiliations

  1. Aeronautics Institute of Technology, Sao Jose dos Campos, SP, Brazil

    Roberto Douglas Guimarães de Aquino, Vitor Venceslau Curtis & Filipe Alves Neto Verri

  2. Federal University of Sao Paulo, Sao Jose dos Campos, SP, Brazil

    Roberto Douglas Guimarães de Aquino

Authors
  1. Roberto Douglas Guimarães de Aquino
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  2. Vitor Venceslau Curtis
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  3. Filipe Alves Neto Verri
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Corresponding author

Correspondence to Roberto Douglas Guimarães de Aquino .

Editor information

Editors and Affiliations

  1. Federal University of São Carlos, São Carlos, Brazil

    Murilo C. Naldi

  2. Centro Universitario da FEI, São Bernardo do Campo, Brazil

    Reinaldo A. C. Bianchi

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de Aquino, R.D.G., Curtis, V.V., Verri, F.A.N. (2023). A Clustering Validation Index Based on Semantic Description. In: Naldi, M.C., Bianchi, R.A.C. (eds) Intelligent Systems. BRACIS 2023. Lecture Notes in Computer Science(), vol 14197. Springer, Cham. https://doi.org/10.1007/978-3-031-45392-2_21

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  • DOI: https://doi.org/10.1007/978-3-031-45392-2_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-45391-5

  • Online ISBN: 978-3-031-45392-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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