Reconstruction of missing data in social network Based on Affinity Propagation

被引：0
|
作者：
Liu, Rongxin [1 ]
Liu, Qun [2 ]
机构：
[1] Chongqing Univ Posts & Telecommun Univ, Key Lab Computat Intelligence, Chongqing 400065, Peoples R China
[2] Chongqing Univ Posts & Telecommun Univ, Sch Comp Technol, Chongqing 400065, Peoples R China
来源：
PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON MECHATRONICS, MATERIALS, CHEMISTRY AND COMPUTER ENGINEERING 2015 (ICMMCCE 2015) | 2015年 / 39卷
关键词：
Network Topology; social networks; affinity propagation; missing data recovery;
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：
With the appearance of data explosion, important data in incomplete network could be missed caused by some factors. To address the problem, we present a reconstruction framework based on Hawkes process with self-exciting and TAP (Topical affinity propagation) to effectively and efficiently reconstruct data. The existing methods mainly focus on how to replace missing values with some plausible estimate, but do not consider reconstruction efficiency and dynamic network. In our paper, we analyze temporal patterns and affinity propagation in the series of interactive events between nodes.
引用
收藏
页码：2483 / 2486
页数：4
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