Abstract
This paper identifies the main criteria used by architecture specialists in the task of clustering alternative floor plan designs. It shows how collective actions of respondents lead to their clustering by carrying out an online exercise. The designs were randomly pre-generated by a hybrid evolutionary algorithm and a questionnaire was posed in the end for the respondents to indicate which similarity criteria they have used. A network of designs was then obtained and it was partitioned into clusters using a modularity optimization algorithm. The results show that the main criterion used was the internal arrangement of spaces, followed by overall shape and by external openings orientation. This work allows the future development of novel algorithms for automatic classification, clustering, and database retrieval of architectural floor plans.
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Acknowledgements
Sousa-Rodrigues, D. was partially supported by project Topdrim FP7-ICT-2011-8/318121. Rodrigues, E., Gaspar, A.R., and Gomes, Á. were partially supported by project Automatic Generation of Architectural Floor Plans with Energy Optimization (GerAPlanO), QREN 38922, CENTRO-07-0402-FEDER-038922 and framed under the Energy for Sustainability Initiative at University of Coimbra.
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Sousa-Rodrigues, D., de Sampayo, M.T., Rodrigues, E., Gaspar, A.R., Gomes, Á. (2015). Crowdsourced Clustering of Computer Generated Floor Plans. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2015. Lecture Notes in Computer Science(), vol 9320. Springer, Cham. https://doi.org/10.1007/978-3-319-24132-6_17
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DOI: https://doi.org/10.1007/978-3-319-24132-6_17
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