Paper Info
Title
Analysis of GSM calls data for understanding user mobility behavior
Abstract
This information about our GSM calls is stored by the TelCo operator in large volumes and with strict privacy constraints making it challenging the analysis of these fingerprints for inferring mobility behavior. This paper proposes a strategy for mobility behavior identification based on aggregated calling profiles of mobile phone users. This compact representation of the user call profiles is the input of the mining algorithm for automatically classifying various kinds of mobility behavior. A further advantage of having defined the call profiles is that the analysis phase is based on summarized privacy-preserving representation of the original data. We show how these call profiles permit to design a two step process - implemented into a system - based on a bootstrap phase and a running phase for classifying users into behavior categories. We evaluated the system in two case studies where individuals are classified into residents, commuters and visitors. We conclude the paper with a discussion which emphasizes the role of the call profiles for the design of a new collaboration model between data provider and data analyst.
Year
DOI
Venue
2013
10.1109/BigData.2013.6691621
Silicon Valley, CA
Keywords
DocType
ISSN
cellular radio,data analysis,data mining,data privacy,pattern classification,telecommunication computing,GSM calls data,Global System for Mobile Communications,analysis phase,behavior categories,bootstrap phase,call profiles,commuters,data analysis,data provider,fingerprint analysis,mining algorithm,mobility behavior classification,mobility behavior identification,privacy constraints,privacy-preserving representation,residents,running phase,user call profiles,user mobility behavior,visitors
Conference
2639-1589
Citations 
PageRank 
References 
11
0.74
5
Authors
4
Name
Order
Citations
PageRank
Barbara Furletti1807.87
Lorenzo Gabrielli210910.41
Chiara Renso392576.04
Salvatore Rinzivillo467344.49