An efficient method for mining the maximal α-quasi-clique-community of a given node in complex networks
Bibliographic Data
| ID | 4619244 |
|---|---|
| Authors | Patricia Conde-Cespedes (0000-0002-6208-3046, Institut Supérieur d'Électronique de Paris, corresponding author), Blaise Ngonmang (Université Sorbonne Paris Nord), Emmanuel Viennet (0009-0004-0922-2934, Université Sorbonne Paris Nord) |
| Year | 2018 |
| Volume | 8 |
| Issue | 1 |
| Pages | 20 |
| Publication date | 2018-12-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Network Analysis and Mining (JOURNAL) |
| Journal identifiers | ISSN: 1869-5450 • E-ISSN: 1869-5469 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13278-018-0497-y |
| OpenAlex | W2790753431 |
| Language | EN |
| Citations received | 1 |
| References cited | 37 |
Clique · Clique percolation method · Combinatorics · Community structure · Complex network · Machine learning · Advanced Graph Neural Networks · Complex Network Analysis Techniques · Computer Science · Graph theory and applications · Mathematics · Theoretical Computer Science
Benchmark graphs for testing community detection algorithms
Resolution limit in community detection
Community detection in graphs
Finding and evaluating community structure in networks
Community structure in social and biological networks
Fast unfolding of communities in large networks
A Procedure for Clique Detection Using the Group Matrix
An Information Flow Model for Conflict and Fission in Small Groups
| Unique citing works | 1 |
|---|---|
| Citations per year | 0.17 |
| Citation span | 2020 - 2020 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |