Hyperbolic graph generator

Hyperbolic Graph Generator

Networks representing many complex systems in nature and society share some common structural properties like heterogeneous degree distributions and strong clustering. Recent research on network geometry has shown that those real networks can be adequately modeled as random geometric graphs in hyperbolic spaces. In this paper, we present a computer program to generate such graphs. Besides real-...

A Scalable Acyclic Graph Generator

Data generators play an important role in algorithm design and optimization engineering. They are an important tool for modeling, benchmarking, scalability, and cost estimation. Graph generators have been an extensive area of research in last decade. With the unprecendented growth in Internet, WWW, and, social networks there was an immediate need to model and subsequently build generators that ...

Hybed: Hyperbolic Neural Graph Embedding

Neural embeddings have been used with great success in Natural Language Processing (NLP). They provide compact representations that encapsulate word similarity and attain state-of-the-art performance in a range of linguistic tasks. The success of neural embeddings has prompted significant amounts of research into applications in domains other than language. One such domain is graph-structured d...

An Intelligent Example-Generator for Graph Theory

Random Graph Generator for Bipartite Networks Modeling

The purpose of this article is to introduce a new iterative algorithm with properties resembling real life bipartite graphs. The algorithm enables us to generate wide range of random bigraphs, which features are determined by a set of parameters. We adapt the advances of last decade in unipartite complex networks modeling to the bigraph setting. This data structure can be observed in several si...