An algorithm to compute data diversity index in spatial networks

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dc.contributorAnálisis y Visualización de Datos en Redes (ANVIDA)es_ES
dc.contributor.authorAgryzkov, Taras-
dc.contributor.authorTortosa, Leandro-
dc.contributor.authorVicent, Jose F.-
dc.contributor.otherUniversidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificiales_ES
dc.identifier.citationApplied Mathematics and Computation. 2018, 337: 63-75. doi:10.1016/j.amc.2018.04.068es_ES
dc.identifier.issn0096-3003 (Print)-
dc.identifier.issn1873-5649 (Online)-
dc.description.abstractDiversity is an important measure that according to the context, can describe different concepts of general interest: competition, evolutionary process, immigration, emigration and production among others. It has been extensively studied in different areas, as ecology, political science, economy, sociology and others. The quality of spatial context of the city can be gauged through this measure. The spatial context with its corresponding dataset can be modelled using spatial networks. Consequently, this allows us to study the diversity of data present in this specific type of networks. In this paper we propose an algorithm to measure diversity in spatial networks based on the topology and the data associated to the network. In the experiments developed with networks of different sizes, it is observed that the proposed index is independent of the size of the network, but depends on its topology.es_ES
dc.description.sponsorshipPartially supported by the Spanish Government, Ministerio de Economía y Competividad, grant number TIN2017-84821-P.es_ES
dc.rights© 2018 Elsevier Inc.es_ES
dc.subjectDiversity indexes_ES
dc.subjectSpatial networkses_ES
dc.subjectUrban networkses_ES
dc.subjectSpatial statisticses_ES
dc.subjectGini–Simpson indexes_ES
dc.subject.otherCiencia de la Computación e Inteligencia Artificiales_ES
dc.titleAn algorithm to compute data diversity index in spatial networkses_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-84821-P-
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