A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf
.
Generating Scaled Replicas of Real-World Complex Networks
[chapter]
2016
Studies in Computational Intelligence
Research on generative models plays a central role in the emerging field of network science, studying how statistical patterns found in real networks can be generated by formal rules. During the last two decades, a variety of models has been proposed with an ultimate goal of achieving comprehensive realism for the generated networks. In this study, we (a) introduce a new generator, termed ReCoN; (b) explore how models can be fitted to an original network to produce a structurally similar
doi:10.1007/978-3-319-50901-3_2
fatcat:v7nqxl4o55c6bifoxr2aa4hpzm