DocumentCode :
3717234
Title :
City users´ classification with mobile phone data
Author :
Lorenzo Gabrielli;Barbara Furletti;Roberto Trasarti;Fosca Giannotti;Dino Pedreschi
Author_Institution :
Dep. of Information Engineering, University of Pisa - Italy
fYear :
2015
Firstpage :
1007
Lastpage :
1012
Abstract :
Nowadays mobile phone data are an actual proxy for studying the users´ social life and urban dynamics. In this paper we present the Sociometer, and analytical framework aimed at classifying mobile phone users into behavioral categories by means of their call habits. The analytical process starts from spatio-temporal profiles, learns the different behaviors, and returns annotated profiles. After the description of the methodology and its evaluation, we present an application of the Sociometer for studying city users of one small and one big city, evaluating the impact of big events in these cities.
Keywords :
"Cities and towns","Mobile handsets","Labeling","Iterative closest point algorithm","Robustness","Big data","Electronic mail"
Publisher :
ieee
Conference_Titel :
Big Data (Big Data), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/BigData.2015.7363852
Filename :
7363852
Link To Document :
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