TY - GEN
T1 - Discovering missing links in networks using vertex similarity measures
AU - Chen, Hung Hsuan
AU - Gou, Liang
AU - Zhang, Xiaolong
AU - Giles, C. Lee
PY - 2012
Y1 - 2012
N2 - Vertex similarity measure is a useful tool to discover the hidden relationships of vertices in a complex network. We introduce relation strength similarity (RSS), a vertex similarity measure that could better capture potential relationships of real world network structure. RSS is unique in that is is an asymmetric measure which could be used for a more general purpose social network analysis; allows users to explicitly specify the relation strength between neighboring vertices for initialization; and offers a discovery range parameter could be adjusted by users for extended network degree search. To show the potential of vertex similarity measures and the superiority of RSS over other measures, we conduct experiments on two real networks, a biological network and a coauthorship network. Experimental results show that RSS is better in discovering the hidden relationships of the networks.
AB - Vertex similarity measure is a useful tool to discover the hidden relationships of vertices in a complex network. We introduce relation strength similarity (RSS), a vertex similarity measure that could better capture potential relationships of real world network structure. RSS is unique in that is is an asymmetric measure which could be used for a more general purpose social network analysis; allows users to explicitly specify the relation strength between neighboring vertices for initialization; and offers a discovery range parameter could be adjusted by users for extended network degree search. To show the potential of vertex similarity measures and the superiority of RSS over other measures, we conduct experiments on two real networks, a biological network and a coauthorship network. Experimental results show that RSS is better in discovering the hidden relationships of the networks.
UR - http://www.scopus.com/inward/record.url?scp=84863586199&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863586199&partnerID=8YFLogxK
U2 - 10.1145/2245276.2245305
DO - 10.1145/2245276.2245305
M3 - Conference contribution
AN - SCOPUS:84863586199
SN - 9781450308571
T3 - Proceedings of the ACM Symposium on Applied Computing
SP - 138
EP - 143
BT - 27th Annual ACM Symposium on Applied Computing, SAC 2012
T2 - 27th Annual ACM Symposium on Applied Computing, SAC 2012
Y2 - 26 March 2012 through 30 March 2012
ER -