A literature survey that proposes a multidimensional taxonomy for community detection, introduces a general mathematical formalization accommodating disjoint/overlapping/fuzzy structures, reviews modularity functions and both algorithmic and mathematical programming methods, and discusses benchmark
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
ALCMeans combines Laplacian energy-based automatic center identification with DeepWalk embeddings to perform unsupervised community detection without predefining the number of communities and reports 10-20% higher NMI and ARI than several baselines on benchmark datasets.
citing papers explorer
-
A Survey of Community Detection from an Operations Research Perspective: Taxonomy, Mathematical Formulations, Modularity Functions, and Benchmark Datasets
A literature survey that proposes a multidimensional taxonomy for community detection, introduces a general mathematical formalization accommodating disjoint/overlapping/fuzzy structures, reviews modularity functions and both algorithmic and mathematical programming methods, and discusses benchmark