Random Walk Features
Random Walk Features is a graph feature engineering method that generates node or graph representations by extracting statistical patterns from sequences of vertices traversed through stochastic walks, distinguishing it from other feature extraction techniques by its reliance on the topological dynamics of probabilistic paths.
37
Publications
1.4K
Citations
102
Authors
67
Institutions
Publications per year
2017–2026
12
Parents
37
Quantum quincunx in cavity quantum electrodynamics
Barry C. Sanders, Stephen D. Bartlett, Ben Tregenna et al. · Physical Review A · 2003 · 175 citations · Full text
Smoothing clickthrough data for web search ranking
Jianfeng Gao, Wei Yuan, Xiao Li et al. · 2009 · 91 citations
Query suggestion by constructing term-transition graphs
Yang Song, Dengyong Zhou, Li-wei He · 2012 · 65 citations
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University of California, Los Angeles
Los Angeles, United States
2 h-index
4 publications
95 citations
University of Ulster
Coleraine, United Kingdom
2 h-index
7 publications
125 citations
Swiss Finance Institute
Zurich, Switzerland
2 h-index
2 publications
52 citations
University of Southern California
Los Angeles, United States
2 h-index
3 publications
59 citations
University of Pennsylvania
Philadelphia, United States
2 h-index
4 publications
84 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
7 publications
282 citations
Boston University
Boston, United States
2 h-index
3 publications
93 citations
Georgetown University
Washington, United States
2 h-index
4 publications
84 citations
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PROC · 2 publications · 42 citations
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PRA · 2 publications · 225 citations
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1 publications · 47 citations
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PRE · 1 publications · 54 citations
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Repository · 1 publications · 15 citations
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