Abstract The Artificial Benchmark for Community Detection (ABCD) graph is a recently
introduced random graph model with community structure and power-law distribution for …

Abstract The Artificial Benchmark for Community Detection (ABCD) graph is a random graph
model with community structure and power-law distribution for both degrees and community …

Community Detection Algorithm Using Hypergraph Modularity | SpringerLink Skip to main
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Graph embedding is a transformation of nodes of a graph into a set of vectors. A good
embedding should capture the graph topology, node-to-node relationship and other relevant …

Community detection is a classic problem in network science with extensive applications in
various fields. Among numerous approaches, the most common method is modularity …

In this paper, we investigate properties and performance of synthetic random graph models
with a built-in community structure. Such models are important for evaluating and tuning …

The A rtificial B enchmark for C ommunity D etection graph (ABCD) is a random graph model
with community structure and power-law distribution for both degrees and community sizes …

Numerous works have been proposed to generate random graphs preserving the same
properties as real-life large-scale networks. However, many real networks are better …

Graph management systems have become popular for storing and querying graph-oriented
data, and they are often evaluated with benchmarks based on large-scale graphs. However …

Graph embedding is a transformation of nodes of a network into a set of vectors. A good
embedding should capture the underlying graph topology and structure, node-to-node …