Call detail records to characterize usages and mobility events of phone users

Inferring Unusual Crowd Events from Mobile Phone Call Detail Records

The pervasiveness and availability of mobile phone data offer the opportunity of discovering usable knowledge about crowd behavior in urban environments. Cities can leverage such knowledge to provide better services (e.g., public transport planning, optimized resource allocation) and safer environment. Call Detail Record (CDR) data represents a practical data source to detect and monitor unusua...

Statistical Analysis of ATM Call Detail Records

Network management is a problem that faces designers and operators of any type of network. Conventional methods of capacity planning or configuration management are difficult to apply directly to networks that dynamically allocate resources, such as Asynchronous Transfer Mode (ATM) networks and emerging Internet Protocol (IP) networks employing Differentiated Services (DiffServ). This work show...

Event Detection Based on Call Detail Records

In this paper we propose the model of the inhomogeneous Poisson for call frequency and inhomogeneous exponential distribution for call durations to detect events based on mobile phone call detail records. The maximum likelihood method is used to estimate the rate of frequency and call duration. This work is useful for enhancing homeland security, detecting unwanted calls (e.g., spam) and commer...

Clustering Anonymized Mobile Call Detail Records to Find Usage Groups

Exploring the Mobility of Mobile Phone Users

Mobile phone datasets allow for the analysis of human behavior on an unprecedented scale. The social network, temporal dynamics and mobile behavior of mobile phone users have often been analyzed independently from each other using mobile phone datasets. In this article, we explore the connections between various features of human behavior extracted from a large mobile phone dataset. Our observa...