DAZIO: detecting activity zones based on input/output call and SMS activity

Descripción del Articulo

Mobile telecoms operators possess an enormous quantity of data, which could be used to reduce the cost of installing new infrastructure, to provide a better QoS or to plan their infrastructure. Thus, they are concerned to model, understand and predict SMS and calls activity levels in their infrastru...

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Detalles Bibliográficos
Autores: Núñez del Prado, Miguel, Luna, Ana, Gauthier, Romain
Formato: documento de trabajo
Fecha de Publicación:2016
Institución:Universidad del Pacífico
Repositorio:UP-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.up.edu.pe:11354/1825
Enlace del recurso:http://hdl.handle.net/11354/1825
Nivel de acceso:acceso abierto
Materia:Telecomunicaciones
Teléfonos celulares
Descripción
Sumario:Mobile telecoms operators possess an enormous quantity of data, which could be used to reduce the cost of installing new infrastructure, to provide a better QoS or to plan their infrastructure. Thus, they are concerned to model, understand and predict SMS and calls activity levels in their infrastructures. Besides, SMS and call activities analysis can open new business opportunities for geomarketing as well as trade area analysis. In the present effort, we detected activity zones with a difference of only 0.5 km from the reference activity areas extracted from Geo-tweets. We also used Markov chains to represent and predict SMS and call activity levels, achieving a prediction success rate between 80% and 90%.
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