Feb.) Cisco visual networking index : Global mobile data trac forecast update, 2013. ,
From routine to network deployment for data ooading in metropolitan areas, Proc. of IEEE SECON, 2014. ,
Uncovering individual and collective human dynamics from mobile phone records, Journal of Physics A: Mathematical and Theoretical, vol.41, issue.22, 2008. ,
DOI : 10.1088/1751-8113/41/22/224015
A Tale of One City: Using Cellular Network Data for Urban Planning, IEEE Pervasive Computing, vol.10, issue.4, p.1826, 2011. ,
DOI : 10.1109/MPRV.2011.44
Cellphones now used more for data than for calls, 2010. ,
Classifying call proles in large-scale mobile trac datasets, Proc. of IEEE Infocom, 2014. ,
Anomaly detection in a mobile communication network, Computational and Mathematical Organization Theory, vol.22, issue.4, p.407422, 2007. ,
DOI : 10.1007/s10588-007-9018-7
Content consumption cartography of the paris urban region using cellular probe data, Proceedings of the first workshop on Urban networking, UrbaNe '12, 2012. ,
DOI : 10.1145/2413236.2413246
URL : https://hal.archives-ouvertes.fr/hal-01131516
Alcatel-lucent 9900 wireless network guardian, White Paper, 2012. ,
Understanding trac dynamics in cellular data networks, Proc. of IEEE Infocom, 2011. ,
DOI : 10.1109/infcom.2011.5935313
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.360.544
Hexagon mosaic maps for displaying univariate and bivariate geographical data, Cartography & Geographical Information Systems, vol.19, p.228236, 1992. ,
On clustering validation techniques, Journal of Intelligent Information Systems, vol.17, issue.2-3, p.107145, 2001. ,
A statistical method for evaluating systematic relationships, p.14091438, 1958. ,
An examination of procedures for determining the number of clusters in a data set, Psychometrika, vol.77, issue.2, p.159179, 1985. ,
DOI : 10.1007/BF02294245
A fuzzy relative of the isodata process and its use in detecting compact wellseparated clusters, Journal of Cybernetics, vol.3, issue.3, p.3257, 1973. ,
A Criterion for Determining the Number of Groups in a Data Set Using Sum-of-Squares Clustering, Biometrics, vol.44, issue.1, p.2234, 1988. ,
DOI : 10.2307/2531893
Quality Scheme Assessment in the Clustering Process, Proc. of the 4th European Conf. on Principles of Data Mining and Knowledge Discovery, 2000. ,
DOI : 10.1007/3-540-45372-5_26
Silhouettes: A graphical aid to the interpretation and validation of cluster analysis, Journal of Computational and Applied Mathematics, vol.20, issue.1, p.5365, 1987. ,
DOI : 10.1016/0377-0427(87)90125-7
Know Thy Neighbor: Towards Optimal Mapping of Contacts to Social Graphs for DTN Routing, 2010 Proceedings IEEE INFOCOM, 2010. ,
DOI : 10.1109/INFCOM.2010.5462135
Goodness-of-Fit-Techniques, 1986. ,
on the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling, Philosophical Magazine Series, vol.5, issue.50 302, p.157175, 1900. ,
Measurement-driven mobile data trac modelling in a large metropolitan area ,
On a measure of divergence between two statistical populations dened by their probability distributions, Bulletin of the Calcutta Mathematical Society, vol.35, p.99109, 1943. ,
Kernel-based object tracking, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.25, issue.5, p.564577, 2003. ,
DOI : 10.1109/TPAMI.2003.1195991
A self organizing maps model for outlier detection in call data from mobile telecommunication networks, Proc. of the Southern Africa Telecommunication Networks and Applications Conference (SATNAC), 2004. ,
Clustering anonymized mobile call detail records to nd usage groups, Pervasive and Urban Applications (PURBA), 2011. ,
Dierences in phone use between men and women : Quantitative evidence from rwanda, Proceedings of the Fifth International Conference on Information and Communication Technologies and Development, ser. ICTD '12, p.297306, 2012. ,
Mobile data ooading : How much can wi deliver ? Networking, RR IEEE/ACM Transactions on, vol.8613, issue.21 2, p.536550, 2013. ,
DOI : 10.1109/tnet.2012.2218122
Proling users in a 3g network using hourglass co-clustering, Proc. of ACM MobiCom, 2010. ,
A holistic framework for the study of urban traces and the proling of urban processes and dynamics, Proc. of Int. IEEE Conf. on Intelligent Transportation Systems (ITSC), 2009. ,
Identication and characterization of human behavior patterns from mobile phone data, Proc. of NetMob, 2013. ,
Computing urban mobile landscapes through monitoring population density based on cellphone chatting, Int. Journal of Design and Nature and Ecodynamics, vol.3, 2008. ,
Towards estimating the presence of visitors from the aggragate mobile phone network activity they generate, Proc. of Intl. Conference on Computers in Urban Planning and Urban Management, 2009. ,
Mobile customer clustering analysis based on call detail records, Communications of the IIMA, 2007. ,