Abstract
The purpose of BARCODE HOUSING SYTEM, a research project developed over the last four years, has been to create an Internet-based system which facilitates the interaction of the different actors involved in the design, construction and use of affordable housing built with industrialized methods. One of the components of the system is an environment which enables different users – architects, clients, developers – to retrieve the housing units generated by a rule-based engine and stored in a repository. Currently, the repository contains over 10,000 housing units. In order to access this information, we have developed clustering techniques based on self-organizing maps and k-means methods.
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Sicilia, Á., Madrazo, L., González, M. (2011). Applying Clustering Techniques to Retrieve Housing Units from a Repository. In: Gero, J.S. (eds) Design Computing and Cognition ’10. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0510-4_21
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DOI: https://doi.org/10.1007/978-94-007-0510-4_21
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