Output details
11 - Computer Science and Informatics
University College London
Output title
Media Sharing based on Colocation Prediction in Urban Transport
Type
E - Conference contribution
Name of conference/published proceedings
Proc. of 14th ACM International Conference on Mobile Computing and Networking
Volume number
-
Issue number
-
First page of article
58
ISSN of proceedings
-
Year of publication
2008
URL
-
Number of additional authors
2
Additional information
<06>Using digital traces of over 1 million journeys done in the London tube system, this work was the first to show how to effectively share media on the go, using short-range connectivity like Bluetooth. Other protocols had been proposed to tame the same problem, but they failed on reality check (e.g., they assumed content could be transferred instantaneously). This work was the first to propose an algorithm that mines historical periods of co-location among people in a urban setting to predict duration of future encounters, thus engaging in content sharing only when it is likely to succeed. Acceptance Rate: 11.7%
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
35
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
