Articles producció científica> Enginyeria Química

Structural Patterns in Complex Systems Using Multidendrograms

  • Dades identificatives

    Identificador: imarina:3660818
    Autors:
    Gomez, SergioFernandez, AlbertoGranell, ClaraArenas, Alex
    Resum:
    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.
  • Altres:

    Autor segons l'article: Gomez, Sergio; Fernandez, Alberto; Granell, Clara; Arenas, Alex
    Departament: Enginyeria Informàtica i Matemàtiques Enginyeria Química
    e-ISSN: 1099-4300
    Autor/s de la URV: Arenas Moreno, Alejandro / Fernández Sabater, Alberto / Gómez Jiménez, Sergio
    Paraules clau: Uniqueness Patterns in networks Hierarchical clustering Dendrogram
    Resum: 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.
    Àrees temàtiques: 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
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 10994300
    Adreça de correu electrònic de l'autor: alberto.fernandez@urv.cat sergio.gomez@urv.cat alexandre.arenas@urv.cat
    Identificador de l'autor: 0000-0002-1241-1646 0000-0003-1820-0062 0000-0003-0937-0334
    Pàgina final: 5474
    Data d'alta del registre: 2024-09-28
    Volum de revista: 15
    Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
    Enllaç font original: https://www.mdpi.com/1099-4300/15/12/5464
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referència a l'article segons font original: Entropy. 15 (12): 5464-5474
    Referència 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 de l'article: 10.3390/e15125464
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2013
    Pàgina inicial: 5464
    Tipus de publicació: Journal Publications
  • Paraules clau:

    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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