GloDyNE: Global Topology Preserving Dynamic Network Embedding (Extended Abstract)

Hou，Chengbin1,2; Zhang，Han2; He，Shan2; Tang，Ke1

10.1109/ICDE53745.2022.00149

2022

38th IEEE International Conference on Data Engineering (ICDE)

1084-4627

978-1-6654-0884-4

Proceedings - International Conference on Data Engineering

2022-May

1545-1546

9-12 May 2022

Kuala Lumpur, Malaysia

10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA

IEEE COMPUTER SOC

Dynamic Network Embedding (DNE) is attracting much attention due to the time-evolving nature of many real-world networks. The main objective of DNE is to efficiently update node embeddings while preserving network topology at each timestep. The idea of most existing DNE methods is to capture the topological changes at or around the most affected nodes (instead of all nodes) and accordingly update node embeddings. Unfortunately, this kind of approximation, although can improve efficiency, cannot effectively preserve the global topology of a dynamic network at each timestep, due to not considering the inactive sub-networks that receive accumulated topological changes propagated via the high-order proximity. To address this issue, we propose a new DNE method for better global topology preservation. Extensive experiments demonstrate the effectiveness and efficiency of the proposed method.

Dynamic Network Embedding Global Topology

第一

英语

CPCI-S ; EI

Computer Science

Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Theory & Methods

WOS:000855078401073

20223512637503

Efficiency ; Topology

Artificial Intelligence:723.4 ; Production Engineering:913.1 ; Combinatorial Mathematics, Includes Graph Theory, Set Theory:921.4

2-s2.0-85136412606

Scopus

1.Southern University of Science and Technology,Department of Computer Science and Engineering,Shenzhen,China
2.School of Computer Science,University of Birmingham,Birmingham,United Kingdom

Hou，Chengbin,Zhang，Han,He，Shan,et al. GloDyNE: Global Topology Preserving Dynamic Network Embedding (Extended Abstract)[C]. 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA:IEEE COMPUTER SOC,2022:1545-1546.