Human interaction discovery in smartphone proximity networks

Since humans are fundamentally social beings and interact frequently with others in their daily life, understanding social context is of primary importance in building context-aware applications. In this paper, using smartphone Bluetooth as a proximity sensor to create social networks, we present a probabilistic approach to mine human interaction types in real life. Our analysis is conducted on Bluetooth data continuously sensed with smartphones for over one year from 40 individuals who are professionally or personally related. The results show that the model can automatically discover a variety of social contexts. We objectively validated our model by studying its predictive and retrieval performance.


Published in:
Personal And Ubiquitous Computing, 17, 3, 413-431
Year:
2013
Publisher:
London, Springer London Ltd
ISSN:
1617-4909
Laboratories:




 Record created 2013-03-28, last modified 2018-03-17


Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)