Toward a route detection method base on detail call records
In the last years, smartphones have become the major device for communication enabling Telco operators to capture subscribers’ whereabouts. This location information allows computing eostatistics to study transportation systems, traffic jams, origin-destination matrix, etc. The first task to accompl...
Guardado en:
| Autores principales: | , |
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| Formato: | Documento de trabajo |
| Lenguaje: | Inglés |
| Publicado: |
Universidad del Pacífico. Centro de Investigación
2016
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/11354/1824 http://biblioteca.clacso.edu.ar/gsdl/cgi-bin/library.cgi?a=d&c=pe/pe-014&d=113541824oai |
| Aporte de: |
| Sumario: | In the last years, smartphones have become the major device for communication enabling Telco operators to capture subscribers’ whereabouts. This location information allows computing eostatistics to study transportation systems, traffic jams, origin-destination matrix, etc. The first task to accomplish the aforementioned objectives is to detect routes that people use to go from A to B. Thus, in the present effort, we propose a method to extract automatically routes from CDR data relying on clustering and community detection algorithms. |
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