Document - Improving population estimation from mobile calls: A clustering approach

2016

Conference article Restricted

Improving population estimation from mobile calls: A clustering approach

Lulli A., Gabrielli L., Dazzi P., Dell'Amico M., Michiardi P., Nanni M., Ricci L.

Ethernet networks Estimation Production

Statistical authorities promote and safeguard the production and publication of official statistics that serve the public good. One of their duties is to monitor the presence of individuals region by region. Traditionally this activity has been conducted by means of censuses and surveys. Nowadays technologies open new possibilities such as a continuous sensing of the presences by leveraging the data associated to mobile devices, e.g., the behaviour of users on doing calls. In this paper first we propose a specifically conceived similarity function able to capture similarity between individuals call behaviours. Second we make use of a clustering algorithm able to handle arbitrary metric leading to a good internal and external consistency of clusters. The approach provides better population estimation with respect to state of the art comparing with real census data. The scalability and flexibility that characterises the proposed framework enables novel scenarios for the characterization of people by means of data derived from mobile users, ranging from the nearly-realtime estimation of presences to the definition of complex, uncommon user archetypes.

Source: IEEE Symposium on Computers and Communication, pp. 1097–1102, Messina, Italy, 27-30 June 2016

Publisher: IEEE Computer Society Press,, Los Alamitos, Calif. , Stati Uniti d'America

Metrics

Back to previous page

Cite as

BibTeX entry

@inproceedings{oai:it.cnr:prodotti:366252,
	title = {Improving population estimation from mobile calls: A clustering approach},
	author = {Lulli A. and Gabrielli L. and Dazzi P. and Dell'Amico M. and Michiardi P. and Nanni M. and Ricci L.},
	publisher = {IEEE Computer Society Press,, Los Alamitos, Calif. , Stati Uniti d'America},
	doi = {10.1109/iscc.2016.7543882},
	booktitle = {IEEE Symposium on Computers and Communication, pp. 1097–1102, Messina, Italy, 27-30 June 2016},
	year = {2016}
}