夏昊翔
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Using rough set similarity for link prediction in directed network
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Indexed by:期刊论文

Date of Publication:2015-06-01

Journal:ICIC Express Letters

Included Journals:EI、Scopus

Volume:9

Issue:7

Page Number:1997-2002

ISSN No.:1881803X

Abstract:Given the link prediction in directed network, not only the effect of the common neighbors of two nodes but also that of other nodes in the local community should be taken into account. Firstly, the in-set of one node is defined as the tail-node of directed edges starting with it and the out-set of the node is composed by the headnode of directed edges ending with it. So the local community of a directed edge includes the out-set of its head-node and the in-set of its tail-node. Then we present a rough-set similarity index to measure the possibility of a directed edge for link prediction. After the classification of in-set and out-set with the knowledge of out-degree and in-degree, the rough-set similarity can be determined by the proportion of the difference between their upper approximation sets and their lower approximation sets. Finally using two actual examples of microblogging networks we verify the effectiveness of proposed similarity index, by a comparison with four classic indexes for the precision in the condition of complete links and for the predictability in the condition of missing links. ? 2015, ISSN 1881-803X.

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Gender:Male

Alma Mater:大连理工大学

Degree:Doctoral Degree

School/Department:系统工程研究所

Discipline:Management Science and Engineering. Systems Engineering

Business Address:经济管理学院D533

Contact Information:hxxia(at)dlut(dot)edu(dot)cn 电话:0411-84706689

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