| id |
DDSS2006-HB-325 |
| authors |
Jean Oh, Jie-Eun Hwang, Stephen F. Smith, and Kimberle Koile |
| year |
2006 |
| title |
Learning from Main Streets - A machine learning approach identifying neighborhood commercial districts |
| source |
Van Leeuwen, J.P. and H.J.P. Timmermans (eds.) 2006, Innovations in Design & Decision Support Systems in Architecture and Urban Planning, Dordrecht: Springer, ISBN-10: 1-4020-5059-3, ISBN-13: 978-1-4020-5059-6, p. 325-340 |
| summary |
In this paper we explore possibilities for using Artificial Intelligence techniques to boost the performance of urban design tools by providing large scale data analysis and inference capability. As a proof of concept experiment we showcase a novel application that learns to identify a certain type of urban setting, Main Streets, based on architectural and socioeconomic features of its vicinity. Our preliminary experimental results show the promising potential for the use of machine learning in the solving of urban planning problems. |
| keywords |
Main street approach, Community development, Artificial intelligence, Machine learning, Active learning algorithm |
| series |
DDSS |
| full text |
 file.pdf (406,415 bytes) |
| references |
Content-type: text/plain
|
Baldi, P. and Brunak S. (1998)
 Bioinformatics: The Machine Learning Approach
, MIT Press
|
|
|
|
|
Batty, M., M. Dodge, et al. (2000)
New Technologies For Urban Designers: The VENUE Project
, Center for Advanced Spatial Analysis working Paper Series
|
|
|
|
|
Berges, J.C. (1998)
A Tutorial on Support Vector Machines for Pattern Recognition
, Data Mining and Knowledge Discovery, 2(2): 21-167
|
|
|
|
|
Blum, A. and Mitchell, T. (1998)
Combining labeled and unlabeled data with co-training
, Proceedings of the Workshop on Computational Learning Theory, p92-100
|
|
|
|
|
Caniggia, G. and G. Maffei (1979)
Architectural Composition and Building Typology: Integrating Basic Building
, Firenze, Italy, Alinea Editrice
|
|
|
|
|
Canu, S.; Grandvalet, Y.; and Rakotomamonjy, A. (2003)
Svm and kernel methods matlab toolbox
, Perception Systems et Information, INSA de Rouen, Rouen, France
|
|
|
|
|
El-Khoury, R., E. Robbins, et al. (2003)
Shaping the city: studies in history, theory and urban design
, New York, NY 10001, Routledge
|
|
|
|
|
Getoor L. (2001)
Learning Statistical Models from RelationalData
, PhD thesis, Stanford University
|
|
|
|
|
Hillier, B. and Hanson, J. (1984)
The social logic of space
, Cambridge; New York, Cambridge University Press
|
|
|
|
|
Innes, E. J. (1998)
Information in Communicative Planning
, Journal of the American Planning Association, 64(1): 52-63
|
|
|
|
|
Isenberg, A. (2004)
Downtown America: a history of the place and the people who made it
, Chicago, University of Chicago Press: xviii, 441 p., [2] p. of plates (col)
|
|
|
|
|
Joachims, T. (1998)
Text Categorization with Support Vector Machines: Learning with Many Relevant Features
, Lecture Notes in Computer Science, 1398, Springer-Verlag
|
|
|
|
|
Krieger, A. (2004)
Territories of Urban Design
, Harvard Design School
|
|
|
|
|
Krier, R. and C. Rowe (1991)
Urban space
, Academy Editions
|
|
|
|
|
Lopilato, L. (2003)
Main Street: some lessons in revitalization
, University Press of America, New York
|
|
|
|
|
Mitchell, T. M. (1997)
Machine Learning
, McGraw Hill, New York
|
|
|
|
|
Moudon, A. V. (1998)
The changing Morphology of Suburban Neighborhoods
, Typological process and design theory, Aga Khan Program for Islamic Architecture at Harvard University and Massachusetts Institute of Technology
|
|
|
|
|
Needham, B. (1977)
How cities work: an introduction
, Oxford; N.Y., Pergamon Press
|
|
|
|
|
Nguyen, H. T., Smeulders A. (2004)
Active learning using pre-clustering
, Proceedings of International Conference on Machine Learning
|
|
|
|
|
Rapoport, A. (1990)
The meaning of the built environment: a nonverbal communication approach
, Tucson, University of Arizona Press
|
|
|
|
| last changed |
2006/08/29 12:55 |
|
