Modelling and Searching Networks

建模和搜索网络

• 批准号: 418059-2012
• 负责人: Pralat, Pawel
• 金额: $ 1.46万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=530986
• 关键词: Modelling; Searching; Networks

One of the characteristic features of many complex, real-world networks is a power-law degree sequence, in which the fraction of vertices of degree larger than k decreases as a power of k. Since in the standard models of sparse random graphs the fraction of vertices of large degree decreases exponentially with k, a number of new probabilistic models of the web graph have been proposed. Such networks are large-scale, decentralized, and evolve dynamically over time. The last decade has seen a flurry of research on the structure, function, and modelling of complex networks.

许多复杂的现实世界网络的特征之一是幂律度序列，其中度大于k的顶点的比例随着k的幂而减少。由于在稀疏随机图的标准模型中，大度顶点的比例随k呈指数下降，因此已经提出了许多新的网络图的概率模型。此类网络是大规模的、去中心化的，并且随着时间的推移动态发展。在过去的十年里，人们对复杂网络的结构、功能和建模进行了大量的研究。