Compute the edge p-Laplacian centrality for air traffic network
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Abstract (arXiv)
The problem that we would like to solve in this paper is to compute the edge p-Laplacian centrality for the air traffic network. In this problem, instead of computing the edge p-Laplacian centrality directly which is the very hard problem, we convert the air traffic network to the line graph. Finally, we will compute the node p-Laplacian centrality of the line graph which is equivalent to the edge p-Laplacian of the air traffic network. In this paper, the novel un-normalized graph (p-) Laplacian based ranking method will be developed based on the un-normalized graph p-Laplacian operator definitions such as the curvature operator of graph (i.e. the un-normalized graph 1-Laplacian operator) and will be used to compute the node p-Laplacian centrality of the line graph. The results from the experiments show that the un-normalized graph p-Laplacian ranking methods can be implemented successfully.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 28 references that are in the map. First posted on arXiv 13 Dec 2025.
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References · 6
- 2018Hypergraph based semi-supervised learning algorithms applied to speech recognition problem: a novel approachcited by 3
- 2021Noise-robust classification with hypergraph neural networkcited by 2
- 2021Text classification problems via BERT embedding method and graph convolutional neural networkcited by 2
- 2019Solve fraud detection problem by using graph based learning methodscited by 1
- 2019To Detect Irregular Trade Behaviors In Stock Market By Using Graph Based Ranking Methodscited by 1
- 2024Hypergraph Laplacian Eigenmaps and Face Recognition Problemscited by 1
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