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physics.soc-ph2026

Non-Supervised Community Detection and Hierarchical Modularity Estimation in Complex Networks

Alexandre Benatti, Luciano da F. Costa

This work extends to complex networks a recently described methodology (A. Benatti and L. da F Costa, Detecting Hierarchical Clusters and Estimating their Modularity Directly from…

physics.soc-ph2026

Detecting Hierarchical Clusters and Estimating their Modularity Directly from Dendrograms

Alexandre Benatti, Luciano da F. Costa

Identifying possible clusters in datasets and estimating their hierarchical modularity are central tasks in pattern recognition. In the present work, concepts and methodologies are…

physics.soc-ph2025

Random Walks Performed by Topologically-Specific Agents on Complex Networks

Alexandre Benatti, Luciano da F. Costa

Random walks by single-node agents have been systematically conducted on various types of complex networks in order to investigate how their topologies can affect the dynamics of t…

physics.soc-ph2024

Partially Proportional and Adaptive Similarity Indices

Alexandre Benatti, Luciano da F. Costa

A good deal of science and technology concepts and methods rely on comparing and relating entities in quantitative terms. Among the several possible approaches, similarity indices…

physics.soc-ph2024

Agglomerative Clustering in Uniform and Proportional Feature Spaces

Alexandre Benatti, Luciano da F. Costa

Pattern comparison represents a fundamental and crucial aspect of scientific modeling, artificial intelligence, and pattern recognition. Three main approaches have typically been a…

physics.soc-ph2024

Subsuming Complex Networks by Node Walks

Alexandre Benatti, Luciano da F. Costa

The concept of node walk in graphs and complex networks has been addressed, consisting of one or more nodes that move into adjacent nodes, henceforth incorporating the respective c…