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Author Ficek, M. ♦ Kencl, L.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2010
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science ♦ Natural sciences & mathematics ♦ Physics ♦ Electricity & electronics ♦ Technology ♦ Engineering & allied operations
Subject Keyword agglomerative clustering ♦ GSM ♦ Google ♦ mobility ♦ Poles and towers ♦ Mobile communication ♦ Data mining ♦ tracking ♦ Databases ♦ Computer architecture ♦ Cell-ID ♦ Mobile computing ♦ Reality Mining
Abstract Data captured from a live cellular network with the real users during their common daily routine help to understand how the users move within the network. Unlike the simulations with limited potential or expensive experimental studies, the research in user-mobility or spatio-temporal user behavior can be conducted on publicly available datasets such as the Reality Mining Dataset. These data have been for many years a source of valuable information about social interconnection between users and user-network associations. However, an important, spatial dimension is missing in this dataset. In this paper, we present a methodology for retrieving geographical locations matching the GSM cell identifiers in the Reality Mining Dataset, an approach base on querying the Google Location API. A statistical analysis of the measure of success of locations retrieval is provided. Further, we present the LAC-clustering method for detecting and removing outliers, a heuristic extension of general agglomerative hierarchical clustering. This methodology enables further, previously impossible analysis of the Reality Mining Dataset, such as studying user mobility patterns, describing spatial trajectories and mining the spatio-temporal data.
Description Author affiliation: R&D Centre for Mobile Applications, Czech Technical University in Prague, Czech Republic (Ficek, M.; Kencl, L.)
ISBN 9781424474882
ISSN 21556806
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2010-11-08
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781424474905
Size (in Bytes) 1.00 MB
Page Count 8
Starting Page 666
Ending Page 673


Source: IEEE Xplore Digital Library