DocumentCode :
2413465
Title :
GDC: Group Discovery Using Co-location Traces
Author :
Mardenfeld, Steve ; Boston, Daniel ; Pan, Susan Juan ; Jones, Quentin ; Iamntichi, Adriana ; Borcea, Cristian
Author_Institution :
Comput. Sci. Dept., New Jersey Inst. of Technol., Newark, NJ, USA
fYear :
2010
fDate :
20-22 Aug. 2010
Firstpage :
641
Lastpage :
648
Abstract :
Smart phones can collect and share Bluetooth co-location traces to identify ad hoc or semi-permanent social groups. This information, known to group members but otherwise unavailable, can be leveraged in applications and protocols, such as recommender systems or delay-tolerant forwarding in ad hoc networks, to enhance the user experience. Group discovery using Bluetooth co-location is practical because:(i) Bluetooth is embedded in nearly every phone and has low battery consumption, (ii) the short wireless transmission range can lead to good group identification accuracy, and (iii) privacy-conscious users are more likely to share co-location data than absolute location data. This paper proposes the Group Discovery using Co-location traces (GDC) algorithm, which leverages user meeting frequency and duration to accurately detect groups. GDC is validated on one month of data collected from 141 smart phones carried by students on our campus. Users rated GDC´s groups 30% better than groups discovered using the K-Clique algorithm. Additionally, GDC lends itself more easily to a distributed implementation, which achieves similar results with the centralized version while improving user´s privacy.
Keywords :
Bluetooth; ad hoc networks; mobile computing; social networking (online); GDC algorithm; K-Clique algorithm; ad hoc networks; bluetooth colocation traces; delay-tolerant forwarding; group discovery; recommender systems; smart phones; Accuracy; Bluetooth; Facebook; Mobile communication; Protocols; Smart phones; Time frequency analysis; Mobile social computing; co-location traces; group discovery; smart phones;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Social Computing (SocialCom), 2010 IEEE Second International Conference on
Conference_Location :
Minneapolis, MN
Print_ISBN :
978-1-4244-8439-3
Electronic_ISBN :
978-0-7695-4211-9
Type :
conf
DOI :
10.1109/SocialCom.2010.99
Filename :
5591535
Link To Document :
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