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Description
  • 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.
  • 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. (en)
Title
  • Spatial Extension of the Reality Mining Dataset
  • Spatial Extension of the Reality Mining Dataset (en)
skos:prefLabel
  • Spatial Extension of the Reality Mining Dataset
  • Spatial Extension of the Reality Mining Dataset (en)
skos:notation
  • RIV/68407700:21230/10:00172398!RIV11-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 288966
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/10:00172398
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • mobility; tracking; Reality Mining; GSM; Cell-ID; agglomerative clustering (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [09AA37229C36]
http://linked.open...v/mistoKonaniAkce
  • San Francisco, CA
http://linked.open...i/riv/mistoVydani
  • New York
http://linked.open...i/riv/nazevZdroje
  • The 7th IEEE International Conference on Mobile Ad-hoc and Sensor Systems
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Kencl, Lukáš
  • Ficek, Michal
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
https://schema.org/isbn
  • 978-1-4244-7489-9
http://localhost/t...ganizacniJednotka
  • 21230
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