Discovering missing links in networks using vertex similarity measures

Hung Hsuan Chen, Liang Gou, Xiaolong Zhang, C. Lee Giles

研究成果: 書貢獻/報告類型會議論文篇章同行評審

59 引文 斯高帕斯(Scopus)

摘要

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.

原文???core.languages.en_GB???
主出版物標題27th Annual ACM Symposium on Applied Computing, SAC 2012
頁面138-143
頁數6
DOIs
出版狀態已出版 - 2012
事件27th Annual ACM Symposium on Applied Computing, SAC 2012 - Trento, Italy
持續時間: 26 3月 201230 3月 2012

出版系列

名字Proceedings of the ACM Symposium on Applied Computing

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???event.eventtypes.event.conference???27th Annual ACM Symposium on Applied Computing, SAC 2012
國家/地區Italy
城市Trento
期間26/03/1230/03/12

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