Name
Abstract | ||
|---|---|---|
Big Data originating from the digital breadcrumbs of human activities, sensed as by-product of the technologies that we use for our daily activities, allows us to observe the individual and collective behavior of people at an unprecedented detail. Many dimensions of our social life have big data "proxies", such as the mobile calls data for mobility. In this paper we investigate to what extent data coming from mobile operators could be a support in producing reliable and timely estimates of intra-city mobility flows. The idea is to define an estimation method based on calling data to characterize the mobility habits of visitors at the level of a single municipality. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-15201-1_14 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
Big data,Urban population,Inter-city mobility,Data mining | Data science,Collective behavior,Internet privacy,Activities of daily living,Computer science,Real-time computing,Operator (computer programming),Mobile phone,Big data | Conference |
Volume | ISSN | Citations |
8938 | 0302-9743 | 3 |
PageRank | References | Authors |
0.39 | 8 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lorenzo Gabrielli | 1 | 109 | 10.41 |
| Barbara Furletti | 2 | 80 | 7.87 |
| Fosca Giannotti | 3 | 2948 | 253.39 |
| Mirco Nanni | 4 | 1412 | 84.47 |
| Salvatore Rinzivillo | 5 | 673 | 44.49 |