Hypergraph artificial benchmark for community detection (h–ABCD)
Abstract The Artificial Benchmark for Community Detection (ABCD) graph is a recently
introduced random graph model with community structure and power-law distribution for …
introduced random graph model with community structure and power-law distribution for …
Modularity of the ABCD random graph model with community structure
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 …
model with community structure and power-law distribution for both degrees and community …
Evaluating node embeddings of complex networks
A Dehghan-Kooshkghazi, B Kamiński… - Journal of Complex …, 2022 - academic.oup.com
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 …
embedding should capture the graph topology, node-to-node relationship and other relevant …
[HTML][HTML] Artificial benchmark for community detection with outliers (ABCD+ o)
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 …
with community structure and power-law distribution for both degrees and community sizes …
Outliers in the ABCD random graph model with community structure (ABCD+ O)
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 …
with community structure and power-law distribution for both degrees and community sizes …
[图书][B] Generative Methods for Social Media Analysis
This book draws a broad-stroke, panoramic picture of the State of the Art (SoTA) of the
research in generative methods for the analysis of social media data. It fills a void, as the …
research in generative methods for the analysis of social media data. It fills a void, as the …
Self-similarity of Communities of the ABCD Model
The A rtificial B enchmark for C ommunity D etection (ABCD) graph is a random graph model
with community structure and power-law distribution for both degrees and community sizes …
with community structure and power-law distribution for both degrees and community sizes …
[HTML][HTML] Predicting properties of nodes via community-aware features
This paper shows how information about the network's community structure can be used to
define node features with high predictive power for classification tasks. To do so, we define a …
define node features with high predictive power for classification tasks. To do so, we define a …
Network Embedding Exploration Tool (NEExT)
In this paper, we introduce NEExT (N etwork E mbedding Ex ploration T ool) for embedding
collections of graphs via user-defined node features. The advantages of the framework are …
collections of graphs via user-defined node features. The advantages of the framework are …
Modularity based community detection in hypergraphs
In this paper, we make a significant step toward designing a scalable community detection
algorithm using hypergraph modularity function. The main obstacle with adjusting the initial …
algorithm using hypergraph modularity function. The main obstacle with adjusting the initial …