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Multilevel graph embedding
Author(s) -
Quiring Benjamin,
Vassilevski Panayot S.
Publication year - 2021
Publication title -
numerical linear algebra with applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.02
H-Index - 53
eISSN - 1099-1506
pISSN - 1070-5325
DOI - 10.1002/nla.2326
Subject(s) - embedding , scalability , graph embedding , graph , theoretical computer science , mathematics , set (abstract data type) , computer science , artificial intelligence , database , programming language
The goal of the present paper is the design of embeddings of a general sparse graph into a set of points inℝ dfor appropriate d ≥ 2 . The embeddings that we are looking at aim to keep vertices that are grouped in communities together and keep the rest apart. To achieve this property, we utilize coarsening that respects possible community structures of the given graph. We employ a hierarchical multilevel coarsening approach that identifies communities (strongly connected groups of vertices) at every level. The multilevel strategy allows any given (presumably expensive) graph embedding algorithm to be made into a more scalable (and faster) algorithm. We demonstrate the presented approach on a number of given embedding algorithms and large‐scale graphs and achieve speed‐up over the methods in a recent paper.