Inferring social relationships from mobile sensor data

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

While mobile sensors are ubiquitous nowadays, the geographical activities of human beings are feasible to be collected and the geospatial interactions between people can be derived. As we know there is an underlying social network between mobile users, such social relationships are hidden and hold by service providers. Acquiring the social network over mobile users would enable lots of applications, such as friend recommendation and energy-saving mobile DB management. In this paper, we propose to infer the social relationships using the sensor data, which contains the encounter records between individuals, without any knowledge about the real friendships in prior. We propose a two-phase prediction method for the social inference. Experiments conducted on the CRAWDAD data demonstrate the encouraging results with satisfying prediction scores of precision and recall.

Original languageEnglish
Title of host publicationWWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
PublisherAssociation for Computing Machinery, Inc
Pages293-294
Number of pages2
ISBN (Electronic)9781450327459
DOIs
Publication statusPublished - 2014 Apr 7
Event23rd International Conference on World Wide Web, WWW 2014 - Seoul, Korea, Republic of
Duration: 2014 Apr 72014 Apr 11

Publication series

NameWWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web

Other

Other23rd International Conference on World Wide Web, WWW 2014
CountryKorea, Republic of
CitySeoul
Period14-04-0714-04-11

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

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