Crowds - Understanding urban land use from digital footprints of crowds
Description
The established view on semantic organization of space is based on the concept of "land use", which corresponds to an aggregate perspective on the use of an area (e.g. agriculture, residential, business, etc.). The characterization of urban block is built on the human activities that happen there, however a more disaggregated and dynamic view is now possible due to availability of new techniques and technologies. In fact, this should become a more natural way to profile the places. Understanding population dynamics by type, neighborhood, or region would enable customized services (and advertising), as well as the accurate timing of urban service provisions, such as scheduling transit service based on daily, weekly, or monthly mobility demand. In general, more synchronous management of service infrastructures clearly could play an important role in urban mobility management. This fine grained analysis, up to the level of the establishment, makes a big leap in terms of understanding the use of space for the purposes of urban planning and management. In recent work (e.g. [Alves 2009A*, Alves 2009B*]), we have presented several perspectives on extracting semantics of the place from online information. A further step shapes on the intersection of such generic information about space with other digital footprints, such as cell phone usage or taxi demand. An essential scientific contribution of this proposal will be on development of new techniques for land use analysis supported on semantic enriched POIs. Although a substantial number of works evolved along the last years on these topics, in general the means that they use to understand people presence (Erlang measures from mobile operators or geo-referenced photos) were not scrutinized for validity. Our contribution on this topic will be on the correlating these indirect probes with ground truth information on the presence of people, namely using data gathered by the police departments on the number of people attending events like football games or musical happenings. This is a validation step that is essential for the evaluation of the use of indirect means and a second core research goal pursued by the work described in this proposal.Researchers
Carlos Bento (coordinator)
Francisco Câmara Pereira
Ana Cristina da Costa Oliveira Alves
João Oliveirinha
Filipe Rodrigues
Evgheni Polisciuc
Mariana Lourenço
Francisco Nibau Antunes
Francisco Câmara Pereira
Ana Cristina da Costa Oliveira Alves
João Oliveirinha
Filipe Rodrigues
Evgheni Polisciuc
Mariana Lourenço
Francisco Nibau Antunes
Funded by
COMPETE - Programa Operacional Factores de Competitividade (PTDC/EIA-EIA/115014/2009)Partners
Faculdade de Ciências e Tecnologia da Universidade de Coimbra (FCT/UC)Total budget
152 863,00 €Keywords
Pegadas digitais, Pontos de interesse, Enriquecimento semântico de pontos de interesse, Utilização do espaço urbanoStart Date
2011-04-01End Date
2014-03-31Journal Articles
2013
(4 publications)- Rodrigues, F. and Alves, A. and Polisciuc, E. and Jiang, S. and Ferreira, J. and Pereira, F.C. , "Estimating disaggregated employment size from Points-of-Interest and census data: From mining the web to model implementation and visualization", International Journal on Advanced Intelligent Systems, vol. 6, pp. 41-52, 2013
- Rodrigues, F. and Pereira, F.C. and Ribeiro, B. , "Learning from Multiple Annotators: Distinguishing Good from Random Labelers", Pattern Recognition Letters, Elsevier, 2013
- Rodrigues, F. and Pereira, F.C. and Ribeiro, B. , "Sequence labeling with multiple annotators", Machine Learning, Springer, 2013
- Pereira, F.C. and Rodrigues, F. and Ben-Akiva, M. , "Using data from the web to predict public transport arrivals under special events scenarios", Journal of Intelligent Transportation Systems: Technology, Planning, and Operations (JITS), 2013
Conference Articles
2014
(3 publications)- Rodrigues, F. and Pereira, F.C. and Ribeiro, B. , "Gaussian Process Classification and Active Learning with Multiple Annotators", in International Conference on Machine Learning (ICML 2014), 2014
- Geadas, P. and Alves, A. and Ribeiro, B. , " Ensemble Learning for Keyword Extraction from Event Descriptions", in IEEE International Joint Conference on Neural Networks (IJCNN), July 2014, 2014
- Alves, A. and Ferrugento, A. and , M.L. and Rodrigues, F. , "ASAP: Automatic Semantic Alignment for Phrases", in SemEval Workshop, COLING 2014, Ireland, 2014
2012
(2 publications)- Alves, A. and Pereira, F.C. , "Making Sense of Location Context", in 1st International Workshop on Context Discovery and Data Mining part of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , 2012
- Rodrigues, F. and Pereira, F.C. and Alves, A. and Jiang, S. and Ferreira, J. , "Automatic Classification of Points-of-Interest for Land-use Analysis", in GEOProcessing 2012 : The Fourth International Conference on Advanced Geographic Information Systems, Applications, and Services, 2012