Latest Articles for Network Analysis

A look into the importance of network analysis across various fields.

A new method improves analysis of complex systems by focusing on clusters.

A study on effective methods for analyzing bipartite networks through U-statistics.

Learn how ideas spread through networks using graph burning concepts.

Strategies to handle key nodes in various networks effectively.

Methods for local certification of geometric intersection graphs using compact certificates.

Exploring guard strategies in bipartite graphs against attacks.

New algorithm MuLaN enhances analysis of multilayer networks in biology and medicine.

A look into graph theory's algebraic connectivity, focusing on trees and their structures.

This article explores the structure and challenges of degree-equivalent graphs.

A new approach enhances the study of complex networks through efficient curvature computation.

Exploring the role and implications of rainbow cliques in edge-colored graphs.

A look into cospectral graphs and their significance in mathematics and various fields.

Explore boxicity, circular clique graphs, and zero-divisor graphs in graph theory.

This article explores secluded subgraphs and their significance in graph theory.

This article discusses how multiplex networks optimize communication in complex systems.

This article explores the movement through networks and its implications.

Explore how mean subtree order influences graph relationships and structures.

Exploring intrinsic metrics and their significance in understanding graph structures.

A new approach to improve IP alias resolution and dual-stack identification using multiple protocols.

Explore the relationship between combinatorial maps and critical groups in graph theory.

A new algorithm ensures exact shortest paths in changing networks.

Explore the concept of twin-width and its relation to tree-decomposition in graphs.

Exploring the structure and properties of strictly Neumaier graphs.

A new model enhances GNN understanding of node similarities using transitivity.

Explore how networks change over time and their practical applications.

A new model for better interaction predictions in user-item networks.

Study reveals backdoor attack risks in GNN link prediction tasks.

Study the dynamics of flows in signed graphs and their significance.

This method enhances our understanding of network communities through Edge Random Walk Centrality.

New methods improve accuracy and efficiency in predicting network connections.

Unraveling the concept of resistance distance in connected networks.

A tool to improve Wi-Fi signal analysis and human activity recognition.

A new model enhances community search by integrating multi-dimensional edge attributes.

New techniques improve diameter calculations for unit-disk graphs, aiding efficient network analysis.

A new method forecasts the structure of dynamic graphs over time.

A critical look at Eulerian graphs and related indices in research.

New framework tackles challenges in Graph Neural Networks effectively.

Discover how neighbor complexes reveal connections in random graphs.

An overview of unique graph structures and their implications.