Hierarchical community structure preserving approach for network embedding

DOI10.1016/J.INS.2020.09.053zbMath1475.68239OpenAlexW3090598292MaRDI QIDQ2055584

Xian Sun, Jie Tang, Shu Zhao, Zhen Duan, Jie Chen, YanPing Zhang

Publication date: 1 December 2021

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2020.09.053

zbMATH Keywords

network embeddinggranulationrepresentation learninghierarchical community

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Small world graphs, complex networks (graph-theoretic aspects) (05C82) Learning and adaptive systems in artificial intelligence (68T05) Graph theory (including graph drawing) in computer science (68R10) Reasoning under uncertainty in the context of artificial intelligence (68T37)

Uses Software

• LIBLINEAR
• word2vec
• t-SNE
• node2vec
• GraRep
• DeepWalk
• LINE
• Walklets

Cites Work

• Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic
• Sim2vec: node similarity preserving network embedding
• MGRS: a multi-granulation rough set
• Editorial: Granular computing based machine learning in the era of big data
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