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北美退伍军人节(Veterans Day),12 日无更新
arXiv 1003.1883cond-mat.stat-mechcond-mat.dis-nnphysics.soc-ph
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拓扑有偏随机游动及其在网络社区发现中的应用

Topologically biased random walk with application for community finding in networks

Vinko Zlatić, Andrea Gabrielli, Guido Caldarelli

摘要:

提出了无向网络拓扑有偏随机游动的一种新方法。我们专注于一个参数家庭的偏见,并通过使用正式的类比与微扰理论在量子力学,我们调查的特点偏置随机游动。这种类比是通过使用参数运动方程(PEM)来研究随机游动{ \em vs.}参数值。此外,我们还分析了与弛豫速率相关的过渡矩阵的第二本征值的谱隙最大值。这些研究的应用允许{ \em ad hoc}算法用于复杂网络及其社区的探索。

英文摘要:

We present a new approach of topology biased random walks for undirected networks. We focus on a one parameter family of biases and by using a formal analogy with perturbation theory in quantum mechanics we investigate the features of biased random walks. This analogy is extended through the use of parametric equations of motion (PEM) to study the features of random walks {\em vs.} parameter values. Furthermore, we show an analysis of the spectral gap maximum associated to the value of the second eigenvalue of the transition matrix related to the relaxation rate to the stationary state. Applications of these studies allow {\em ad hoc} algorithms for the exploration of complex networks and their communities.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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