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 …
Message-passing on hypergraphs: detectability, phase transitions and higher-order information
Hypergraphs are widely adopted tools to examine systems with higher-order interactions.
Despite recent advancements in methods for community detection in these systems, we still …
Despite recent advancements in methods for community detection in these systems, we still …
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 …
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 …
Comparison of modularity-based approaches for nodes clustering in hypergraphs
V Poda, C Matias - Peer Community Journal, 2024 - peercommunityjournal.org
Statistical analysis and node clustering in hypergraphs constitute an emerging topic
suffering from a lack of standardization. In contrast to the case of graphs, the concept of …
suffering from a lack of standardization. In contrast to the case of graphs, the concept of …
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 …
[PDF][PDF] Supplementary Document for 'A Survey on Hypergraph Mining: Patterns, Tools, and Generators'
In this document, we discuss future applications and directions of hypergraph mining,
especially hypergraph patterns. We mainly review and discuss existing applications and …
especially hypergraph patterns. We mainly review and discuss existing applications and …
ABCD-HN: An Artificial Network Benchmark for Community Detection on Heterogeneous Networks
J Liu, K Guo, L Wu - … on Computer Supported Cooperative Work and …, 2023 - Springer
Community detection is essential for identifying cohesive groups in complex networks.
Artificial benchmarks are critical for evaluating community detection algorithms, offering …
Artificial benchmarks are critical for evaluating community detection algorithms, offering …
Research on the Technology of Virtual Learning Community Detection for Library Information System
L Min - Proceedings of the 2023 7th International Conference …, 2023 - dl.acm.org
Various information systems in libraries generate a large amount of transaction data during
their operation. These data contain rich learning behavior information of learners, as well as …
their operation. These data contain rich learning behavior information of learners, as well as …