Social Network Sampling with Keeping Community Structure

被引：0

作者：

Chang, Wen-Yao ^{[1
]}

Wu, Bang-Ye ^{[1
]}

机构：

[1] Natl Chung Cheng Univ, Dept Comp Sci & Informat Engn, Chiayi, Taiwan

来源：

PROCEEDINGS OF 4TH IEEE INTERNATIONAL CONFERENCE ON APPLIED SYSTEM INNOVATION 2018 ( IEEE ICASI 2018 ) | 2018年

关键词：

social network; graph sampling; community;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Online social networks (OSNs) have become an important way to connect people in recent years. This phenomenon generates lots of interest in graph analysis. Because of the large scale of OSNs, it is almost impossible to perform the research with complete datasets. For some research, i.e. the transition of message, the community structure and shortest path are both important issues. In this paper, we propose a sampling method which can keep the properties of network community structure and shortest paths.

引用

页码：228 / 230

页数：3

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