TY - GEN
T1 - Summarizing the slices
T2 - 15th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2019
AU - Yan, Bo
AU - Tang, Wenli
AU - Liu, Jiamou
AU - Liu, Yiping
AU - Meng, Fanku
AU - Su, Hongyi
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - Core-periphery structure refers to a prevalent property exhibited by many real-world complex networks. The formulation and identification of a network core-periphery structure have been a challenging problem. A classical framework (BE) proposed by Borgatti and Everett defines a core-periphery partition of the network by aligning its nodes with a block model and has been a standard method for this task. This method, however, suffers from high computational costs which make it inapplicable to large networks. Realizing this limitation, we proposed a new framework, which aims to efficiently evaluate core-ness of nodes. Our framework builds a model for core-periphery classification by integrating small samples. The experimental results of six real-world networks shows that our methods can efficiently and effectively identify network core, achieving a running time of less than three hours for a network with about 220, 000 nodes.
AB - Core-periphery structure refers to a prevalent property exhibited by many real-world complex networks. The formulation and identification of a network core-periphery structure have been a challenging problem. A classical framework (BE) proposed by Borgatti and Everett defines a core-periphery partition of the network by aligning its nodes with a block model and has been a standard method for this task. This method, however, suffers from high computational costs which make it inapplicable to large networks. Realizing this limitation, we proposed a new framework, which aims to efficiently evaluate core-ness of nodes. Our framework builds a model for core-periphery classification by integrating small samples. The experimental results of six real-world networks shows that our methods can efficiently and effectively identify network core, achieving a running time of less than three hours for a network with about 220, 000 nodes.
KW - Core periphery
KW - Integration Strategy
KW - Samples
UR - http://www.scopus.com/inward/record.url?scp=85084292675&partnerID=8YFLogxK
U2 - 10.1109/MSN48538.2019.00049
DO - 10.1109/MSN48538.2019.00049
M3 - Conference contribution
AN - SCOPUS:85084292675
T3 - Proceedings - 2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2019
SP - 212
EP - 217
BT - Proceedings - 2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 11 December 2019 through 13 December 2019
ER -