Articles producció científica> Enginyeria Química

Structural Patterns in Complex Systems Using Multidendrograms

  • Datos identificativos

    Identificador: imarina:3660818
    Autores:
    Gomez, SergioFernandez, AlbertoGranell, ClaraArenas, Alex
    Resumen:
    Complex systems are usually represented as an intricate set of relations between their components forming a complex graph or network. The understanding of their functioning and emergent properties are strongly related to their structural properties. The finding of structural patterns is of utmost importance to reduce the problem of understanding the structure¿function relationships. Here we propose the analysis of similarity measures between nodes using hierarchical clustering methods. The discrete nature of the networks usually leads to a small set of different similarity values, making standard hierarchical clustering algorithms ambiguous. We propose the use of multidendrograms, an algorithm that computes agglomerative hierarchical clusterings implementing a variable-group technique that solves the non-uniqueness problem found in the standard pair-group algorithm. This problem arises when there are more than two clusters separated by the same maximum similarity (or minimum distance) during the agglomerative process. Forcing binary trees in this case means breaking ties in some way, thus giving rise to different output clusterings depending on the criterion used. Multidendrograms solves this problem by grouping more than two clusters at the same time when ties occur.
  • Otros:

    Autor según el artículo: Gomez, Sergio; Fernandez, Alberto; Granell, Clara; Arenas, Alex
    Departamento: Enginyeria Informàtica i Matemàtiques Enginyeria Química
    e-ISSN: 1099-4300
    Autor/es de la URV: Arenas Moreno, Alejandro / Fernández Sabater, Alberto / Gómez Jiménez, Sergio
    Palabras clave: Uniqueness Patterns in networks Hierarchical clustering Dendrogram
    Resumen: Complex systems are usually represented as an intricate set of relations between their components forming a complex graph or network. The understanding of their functioning and emergent properties are strongly related to their structural properties. The finding of structural patterns is of utmost importance to reduce the problem of understanding the structure¿function relationships. Here we propose the analysis of similarity measures between nodes using hierarchical clustering methods. The discrete nature of the networks usually leads to a small set of different similarity values, making standard hierarchical clustering algorithms ambiguous. We propose the use of multidendrograms, an algorithm that computes agglomerative hierarchical clusterings implementing a variable-group technique that solves the non-uniqueness problem found in the standard pair-group algorithm. This problem arises when there are more than two clusters separated by the same maximum similarity (or minimum distance) during the agglomerative process. Forcing binary trees in this case means breaking ties in some way, thus giving rise to different output clusterings depending on the criterion used. Multidendrograms solves this problem by grouping more than two clusters at the same time when ties occur.
    Áreas temáticas: Saúde coletiva Physics, multidisciplinary Physics and astronomy (miscellaneous) Physics and astronomy (all) Medicina ii Medicina i Mathematical physics Matemática / probabilidade e estatística Interdisciplinar Information systems Geociências General physics and astronomy Filosofía Engenharias iv Engenharias iii Electrical and electronic engineering Educação física Ciências biológicas i Ciência da computação Astronomia / física
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 10994300
    Direcció de correo del autor: alberto.fernandez@urv.cat sergio.gomez@urv.cat alexandre.arenas@urv.cat
    Identificador del autor: 0000-0002-1241-1646 0000-0003-1820-0062 0000-0003-0937-0334
    Página final: 5474
    Fecha de alta del registro: 2024-09-28
    Volumen de revista: 15
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://www.mdpi.com/1099-4300/15/12/5464
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Entropy. 15 (12): 5464-5474
    Referencia de l'ítem segons les normes APA: Gomez, Sergio; Fernandez, Alberto; Granell, Clara; Arenas, Alex (2013). Structural Patterns in Complex Systems Using Multidendrograms. Entropy, 15(12), 5464-5474. DOI: 10.3390/e15125464
    DOI del artículo: 10.3390/e15125464
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2013
    Página inicial: 5464
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Electrical and Electronic Engineering,Information Systems,Mathematical Physics,Physics and Astronomy (Miscellaneous),Physics, Multidisciplinary
    Uniqueness
    Patterns in networks
    Hierarchical clustering
    Dendrogram
    Saúde coletiva
    Physics, multidisciplinary
    Physics and astronomy (miscellaneous)
    Physics and astronomy (all)
    Medicina ii
    Medicina i
    Mathematical physics
    Matemática / probabilidade e estatística
    Interdisciplinar
    Information systems
    Geociências
    General physics and astronomy
    Filosofía
    Engenharias iv
    Engenharias iii
    Electrical and electronic engineering
    Educação física
    Ciências biológicas i
    Ciência da computação
    Astronomia / física
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