Landing Probabilities of Random Walks for Seed-Set Expansion in Hypergraphs
| Autor: | Pan Li, Eli Chien, Olgica Milenkovic |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Social and Information Networks (cs.SI)
FOS: Computer and information sciences Discrete mathematics Hypergraph Class (set theory) Computer Science - Machine Learning Set expansion Machine Learning (stat.ML) Computer Science - Social and Information Networks Random walk Machine Learning (cs.LG) Computer Science::Discrete Mathematics Statistics - Machine Learning Distortion Tensor Projection (set theory) Mathematics |
| Zdroj: | ITW |
| Popis: | We describe the first known mean-field study of landing probabilities for random walks on hypergraphs. In particular, we examine clique-expansion and tensor methods and evaluate their mean-field characteristics over a class of random hypergraph models for the purpose of seed-set community expansion. We describe parameter regimes in which the two methods outperform each other and propose a hybrid expansion method that uses partial clique-expansion to reduce the projection distortion and low-complexity tensor methods applied directly on the partially expanded hypergraphs. A short version appears in ITW 2021 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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