论文标题
基于多类型Galton-Watson森林的扩散过程的新颖探索
A Novel Exploration of Diffusion Process based on Multi-types Galton-Watson Forests
论文作者
论文摘要
扩散是一种常用的技术，用于在图上从点到点传播信息。扩散背后的理由尚不清楚。多类型Galton-Watson森林是人口增长的随机模型，没有空间或任何其他资源限制。在本文中，我们使用退化的多类型Galton-Watson Forest（MGWF）来解释扩散过程并在它们之间建立等效关系。通过MGWF的两相设置，可以明确解释扩散过程和Google Pagerank系统。它还改善了迭代扩散过程和Google Pagerank系统的收敛行为。我们在提供新的研究方向的同时，通过实验验证该提案。
Diffusion is a commonly used technique for spreading information from point to point on a graph. The rationale behind diffusion is not clear. And the multi-types Galton-Watson forest is a random model of population growth without space or any other resource constraints. In this paper, we use the degenerated multi-types Galton-Watson forest (MGWF) to interpret the diffusion process and establish an equivalent relationship between them. With the two-phase setting of the MGWF, one can interpret the diffusion process and the Google PageRank system explicitly. It also improves the convergence behaviour of the iterative diffusion process and Google PageRank system. We validate the proposal by experiment while providing new research directions.
