2018
DOI: 10.1109/tmc.2017.2722408
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Recurring Contacts between Groups of Devices: Analysis and Application

Abstract: The capability to anticipate a contact with another device can contribute to improving the performance and user satisfaction of mobile social network applications and of any other relying on some form of data harvesting or hoarding. This paper presents a nine year data set of wireless access logs produced by more than 70,000 devices and 40,000 users. Research on the recurring contact patterns observed between groups of devices permitted to model the probabilities of occurrence of a contact at a predefined date… Show more

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Cited by 4 publications
(2 citation statements)
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References 30 publications
(38 reference statements)
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“…Here in this section, we cited different works applying user characteristics to solve challenges in the context of these communication types. Other works included user-provided networks with incentive mechanisms [85], cooperation-based cache [86], extracting social relations from users' ratings [87], and mobility behavior analysis. Online Social Networks research kept appearing linked to cooperative D2D based on social aspects [88], decentralized OSNs [89], and social network analysis methods in behavioral information security.…”
Section: Communicationsmentioning
confidence: 99%
“…Here in this section, we cited different works applying user characteristics to solve challenges in the context of these communication types. Other works included user-provided networks with incentive mechanisms [85], cooperation-based cache [86], extracting social relations from users' ratings [87], and mobility behavior analysis. Online Social Networks research kept appearing linked to cooperative D2D based on social aspects [88], decentralized OSNs [89], and social network analysis methods in behavioral information security.…”
Section: Communicationsmentioning
confidence: 99%
“…For example, various approaches [31], [32], [33] have been proposed to mine users' places of interest and mobility patterns from mobile data. Min et al [7] and Cruz et al [34] analyzed communication logs and wireless access logs respectively to infer users' social relationships. Spolaor et al [35] presented a data extraction tool named DELTA, which can extract UI interaction data for user habit analysis.…”
Section: Personal Knowledge Extractionmentioning
confidence: 99%