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dc.contributor.authorAbarca-Álvarez, Francisco Javier
dc.contributor.authorCampos Sánchez, Francisco Sergio 
dc.contributor.authorMora-Esteban, Rubén
dc.date.accessioned2019-10-30T07:15:24Z
dc.date.available2019-10-30T07:15:24Z
dc.date.issued2019-09-19
dc.identifier.citationAbarca-Alvarez, F.J.; Campos-Sánchez, F.S.; Mora-Esteban, R. Survey Assessment for Decision Support Using Self-Organizing Maps Profile Characterization with an Odds and Cluster Heat Map: Application to Children’s Perception of Urban School Environments. Entropy 2019, 21, 916. [doi:10.3390/e21090916]es_ES
dc.identifier.urihttp://hdl.handle.net/10481/57594
dc.description.abstractThe interpretation of opinion and satisfaction surveys based exclusively on statistical analysis often faces difficulties due to the nature of the information and the requirements of the available statistical methods. These difficulties include the concurrence of categorical information with answers based on Likert scales with only a few levels, or the distancing of the necessary heuristic approach of the decision support system (DSS). The artificial neural network used for data analysis, called Kohonen or self-organizing maps (SOM), although rarely used for survey analysis, has been applied in many fields, facilitating the graphical representation and the simple interpretation of high-dimensionality data. This clustering method, based on unsupervised learning, also allows obtaining profiles of respondents without the need to provide additional information for the creation of these clusters. In this work, we propose the identification of profiles using SOM for evaluating opinion surveys. Subsequently, non-parametric chi-square tests were first conducted to contrast whether answer was independent of each profile found, and in the case of statistical significance (p ≤ 0.05), the odds ratio was evaluated as an indicator of the effect size of such dependence. Finally, all results were displayed in an odds and cluster heat map so that they could be easily interpreted and used to make decisions regarding the survey results. The methodology was applied to the analysis of a survey based on forms administered to children (N = 459) about their perception of the urban environment close to their school, obtaining relevant results, facilitating results interpretation, and providing support to the decision-process.es_ES
dc.description.sponsorshipThis research was funded by Campus de Excelencia Internacional BIOTIC Granada, University of Granada, grant number V1.2015 and the APC was funded by University of Granada.es_ES
dc.language.isoenges_ES
dc.rightsAtribución 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectOpinion surveyses_ES
dc.subjectDecision support systemes_ES
dc.subjectANNes_ES
dc.subjectSelf-Organizing Mapses_ES
dc.subjectOdds ratioes_ES
dc.titleSurvey Assessment for Decision Support Using Self-Organizing Maps Profile Characterization with an Odds and Cluster Heat Map: Application to Children’s Perception of Urban School Environmentses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.3390/e21090916


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Atribución 3.0 España
Except where otherwise noted, this item's license is described as Atribución 3.0 España