Reconstruction of missing data in social network Based on Affinity Propagation

DOI

10.2991/icmmcce-15.2015.478How to use a DOI?

Keywords

Network Topology, social networks, affinity propagation, missing data recovery.

Abstract

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.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Rongxin Liu
AU  - Qun Liu
PY  - 2015/12
DA  - 2015/12
TI  - Reconstruction of missing data in social network Based on Affinity Propagation
BT  - Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.478
DO  - 10.2991/icmmcce-15.2015.478
ID  - Liu2015/12
ER  -