Ramalho Brilhante I, Berlingerio M, Trasarti R, Renso C, Fernandes De Macedo J A, Casanova M A
Graph Mining H.2.8 Database applications. Data mining 58-02 GPS Community
We analyze urban mobility and public places under a new perspective: how can we feature the places in a city based on how people move among them? To answer this question we need to combine places, like points of interest, with mobility information like the trajectories of individuals moving within a city. To accomplish this, we propose a methodology based on complex network analysis: we build a network of points of interests by connecting places by the individual trajectories passing through them. From such network we compute communities finding groups places highly connected by the mobility of the individuals. We present a case study on real trajectory dataset on the city of Milan, showing a complementary view on the urban mobility that is not covered by the state-of-the art techniques on mobility analysis. © 2012 IEEE.
Publisher: IEEE Computer Society
@inproceedings{oai:it.cnr:prodotti:218818, title = {ComeTogether: discovering communities of places in mobility data}, author = {Ramalho Brilhante I and Berlingerio M and Trasarti R and Renso C and Fernandes De Macedo J A and Casanova M A}, publisher = {IEEE Computer Society}, doi = {10.1109/mdm.2012.17}, year = {2012} }