SOOP: Efficient Distributed Graph Computation Supporting Second-Order Random Walks

The second-order random walk has recently been shown to effectively improve the accuracy in graph analysis tasks. Existing work mainly focuses on centralized second-order random walk (SOW) algorithms. SOW algorithms rely on edge-to-edge transition probabilities to generate next random steps. However...

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Bibliographic Details
Published in:	Journal of computer science and technology Vol. 36; no. 5; pp. 985 - 1001
Main Authors:	Niu, Songjie, Zhou, Dongyan
Format:	Journal Article
Language:	English
Published:	Singapore Springer Singapore 01.10.2021 Springer Springer Nature B.V University of Chinese Academy of Sciences,Beijing 100049,China%Bytedance Technology,Beijing 100086,China State Key Laboratory of Computer Architecture,Institute of Computing Technology,Chinese Academy of Sciences Beijing 100190,China
Subjects:	Accuracy Algorithms Analysis Artificial Intelligence Communication Computer Science Data Structures and Information Theory Graphs Information Systems Applications (incl.Internet) Mathematical optimization Optimization techniques Random walk Regular Paper Software Engineering Theory of Computation Transition probabilities second-order PageRank SOOP (second-order random walks with on-demand probability computation) distributed graph computation second-order random walk (SOW) Node2Vec SOOP(second-order random walks with on-demand probability computation)
ISSN:	1000-9000, 1860-4749
Online Access:	Get full text
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