DEGREE AND CLUSTERING COEFFICIENT IN SPARSE RANDOM INTERSECTION GRAPHS

• 成果类型: Article
• 署名作者: Bloznelis, Mindaugas
• 署名单位: Vilnius University
• 刊物名称: ANNALS OF APPLIED PROBABILITY
• ISSN/ISSBN: 1050-5164
• DOI: 10.1214/12-AAP874
• 发表日期: 2013
• 页码: 1254-1289
• 关键词: vertex degree distribution; connectivity; models

摘要

We establish asymptotic vertex degree distribution and examine its relation to the clustering coefficient in two popular random intersection graph models of Godehardt and Jaworski [Electron. Notes Discrete Math. 10 (2001) 129-132]. For sparse graphs with a positive clustering coefficient, we examine statistical dependence between the (local) clustering coefficient and the degree. Our results are mathematically rigorous. They are consistent with the empirical observation of Foudalis et al. [In Algorithms and Models for Web Graph (2011) Springer] that, clustering correlates negatively with degree. Moreover, they explain empirical results on k(-1) scaling of the local clustering coefficient of a vertex of degree k reported in Ravasz and Barabasi [Phys. Rev. E 67 (2003) 026112].