Multiscale Topological Characterization of Dynamic Interaction Patterns in Large-Scale Complex Networks Under Temporal Evolution Constraints

Authors

  • Tomáš Novák Machine Learning Engineer, Czech Republic Author

Keywords:

Complex Networks, Temporal Evolution, Persistent Homology, Multiscale Topology, Community Detection, Network Dynamics, Temporal Motifs

Abstract

The structural evolution of large-scale complex networks over time reveals critical insights into their dynamic behavior and underlying interaction patterns. This study proposes a multiscale topological framework to characterize dynamic interaction patterns in evolving networks constrained by temporal evolution. By integrating temporal motifs, persistence homology, and multiresolution community detection, we demonstrate how topological signatures can be used to trace stability, transitions, and hierarchical organization in dynamic networks. Experiments on synthetic and real-world datasets—including communication and biological networks—highlight the efficiency and scalability of our approach. Our findings establish the methodological foundation for temporal-aware topological analysis in dynamic complex systems

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Published

2020-04-25

How to Cite

Multiscale Topological Characterization of Dynamic Interaction Patterns in Large-Scale Complex Networks Under Temporal Evolution Constraints. (2020). ISCSITR- INTERNATIONAL JOURNAL OF DATA SCIENCE (ISCSITR-IJDS) - ISSN: 3067-7408, 1(1), 1-7. https://iscsitr.in/index.php/ISCSITR-IJDS/article/view/ISCSITR-IJDS_01_01_001