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dc.contributor.authorBove, Giuseppe
dc.contributor.authorRuta, Nicole
dc.contributor.authorMastandrea, Stefano
dc.identifier.citationBove, G., Ruta, N. and Mastandrea, S. (2019) 'Preference Analysis of Architectural Façades by Multidimensional Scaling and Unfolding'. In: Greselin F., Deldossi L., Bagnato L., Vichi M. (eds). Statistical Learning of Complex Data. CLADAG 2017. Studies in Classification, Data Analysis, and Knowledge Organization, pp. 57-64. Springer, Cham.en_US
dc.identifier.isbn978-3-030-21140-0 (online)
dc.identifier.issn2198-3321 (online)
dc.descriptionPaper published in Studies in Classification, Data Analysis, and Knowledge Organization, CLADAG 2017 Conference Proceedings: Statistical Learning of Complex Data , available at:
dc.description.abstractThe methods of paired comparison and ranking play an important role in the analysis of preference data. In this study, first we show how asymmetric multidimensional scaling allows to represent in a diagram the preference order that comes out in a paired-comparison task concerning architectural façades. A ranking task involving the same stimuli and the same subject sample further enriched the preference analysis, because multidimensional unfolding applied to the ranking data matrix allows to detect the relationships between subjects and architectural façades. The results show that high curved façade is the most preferred, followed by the medium curved, angular and rectilinear ones. Rectilinear stimuli were always the least preferred and not angularity as expected.en_US
dc.relation.ispartofseriesStudies in Classification, Data Analysis, and Knowledge Organization
dc.titlePreference Analysis of Architectural Facades by Multidimensional Scaling and Unfoldingen_US
dc.typeConference paperen_US
rioxxterms.funderCardiff Metropolitan Universityen_US
rioxxterms.identifier.projectCardiff Metropolian (Internal)en_US

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    Fovolab aspires to push the boundaries of understanding perceptual experience – how we perceive and are aware of the world.

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