TY - GEN
T1 - Modeling social network relationships via t-cherry junction trees
AU - Proulx, Brian
AU - Zhang, Junshan
PY - 2014/1/1
Y1 - 2014/1/1
N2 - The massive scale of online social networks makes it very challenging to characterize the underlying structure therein. In this paper, we employ the t-cherry junction tree, a very recent advancement in probabilistic graphical models, to develop a compact representation and good approximation of an otherwise intractable model for users' relationships in a social network. There are a number of advantages in this approach: 1) the best approximation possible via junction trees belongs to the class of t-cherry junction trees; 2) constructing a t-cherry junction tree can be largely parallelized; and 3) inference can be performed using distributed computation. To improve the quality of approximation, we also devise an algorithm to build a higher order tree gracefully from an existing one, without constructing it from scratch. We apply this approach to Twitter data containing 100,000 nodes and study the problem of recommending connections to new users.
AB - The massive scale of online social networks makes it very challenging to characterize the underlying structure therein. In this paper, we employ the t-cherry junction tree, a very recent advancement in probabilistic graphical models, to develop a compact representation and good approximation of an otherwise intractable model for users' relationships in a social network. There are a number of advantages in this approach: 1) the best approximation possible via junction trees belongs to the class of t-cherry junction trees; 2) constructing a t-cherry junction tree can be largely parallelized; and 3) inference can be performed using distributed computation. To improve the quality of approximation, we also devise an algorithm to build a higher order tree gracefully from an existing one, without constructing it from scratch. We apply this approach to Twitter data containing 100,000 nodes and study the problem of recommending connections to new users.
UR - http://www.scopus.com/inward/record.url?scp=84904431128&partnerID=8YFLogxK
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U2 - 10.1109/INFOCOM.2014.6848166
DO - 10.1109/INFOCOM.2014.6848166
M3 - Conference contribution
AN - SCOPUS:84904431128
SN - 9781479933600
T3 - Proceedings - IEEE INFOCOM
SP - 2229
EP - 2237
BT - IEEE INFOCOM 2014 - IEEE Conference on Computer Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 33rd IEEE Conference on Computer Communications, IEEE INFOCOM 2014
Y2 - 27 April 2014 through 2 May 2014
ER -