A general model of web graphs
By C. Cooper, Alan M. Frieze. Random Struct. Algorithms, 2003
384 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/887ae82211277f9858cc3e835713920ccc2b9851
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Jure Leskovec
- Christos Faloutsos
- Linyuan Lu
- Jon M. Kleinberg
- Remco van der Hofstad
- Matthew O. Jackson
- Charu C. Aggarwal
- Béla Bollobás
In Information Systems
- Jure Leskovec
- Christos Faloutsos
- Jon M. Kleinberg
- R. Durrett
- Linyuan Lu
- Matthew O. Jackson
- Béla Bollobás
- Michael M. Mitzenmacher
In Statistical and Nonlinear Physics
- Remco van der Hofstad
- Jure Leskovec
- Christos Faloutsos
- Jon M. Kleinberg
- Linyuan Lu
- Matthew O. Jackson
- Michael W. Mahoney
- R. Durrett
Citations in the corpus
- RESILIENCE TO CONTAGION IN FINANCIAL NETWORKS (2011, neutral): “Strong connectivity sparse random directed graphs with prescribed degree sequence has been studied by in Cooper and Frieze (2004). Let λn represent the average degree (then by Condition 3.”
- Growth of preferential attachment random graphs via continuous-time branching processes (2007, methodology): “This model has some overlap with the very general model given in [10] where vertices can be selected preferentially or at random;”
- Random Graphs and Complex Networks (2016, background): “A quite general version of preferential attachment models is presented in [85].”
- Connected Components in Random Graphs with Given Expected Degree Sequences (2002, methodology): “There are also a number of evolution models for generating a powerlaw degree random graphs as in Bollobás, Spencer et al. [11], Cooper and Freeze [17] and Aiello, Chung and Lu [2].”
- A Sequential Importance Sampling Algorithm for Generating Random Graphs with Prescribed Degrees (2011, background): “See [2], [6], [14], [15], [22], and [58] for more information about power-law graphs, where they arise, and ways of generating them.”
- A Brief History of Generative Models for Power Law and Lognormal Distributions (2004, methodology): “For instance, the current arguments based on martingales are much more rigorous than Simon’s approach [12, 16, 38].”
- The Economics of Social Networks (2005, background): “There are other models that are hybrids of random and preferential attachment (e.g., Kleinberg et al (1999), Kumar et al (2000) , Dorogovtsev and Mendes (2001), Levene et al (2002), and Cooper and Frieze (2003)).”
- Distances in Random Graphs with Finite Mean and Infinite Variance Degrees (2005, neutral): “See [2, 3, 4, 7, 8, 9, 10, 11, 15, 26] and the references therein.”
- Mathematical results on scale‐free random graphs (2005, methodology): “Sections 9 and 10 present such results for the 'copying' models of Kumar, Raghavan, Rajagopalan, Sivakumar, Tomkins and Upfal [40], and the very general models defined by Cooper and Frieze [24].”
- Exponential extinction time of the contact process on finite graphs (2012, background): “That the degree distribution of these graphs follows a power law was proved in [9].”
- Graphs over time: densification laws, shrinking diameters and possible explanations (2005, background): “on preferential attachment [2, 3, 10] and the related copying model [18, 19].”