2024/01/25 by Evangelia Tsoukanara, Georgia Koloniari, Tsoukanara, Evangelia +4
Computer Science · Physics and Astronomy · #Complex Network Analysis Techniques #Data Management and Algorithms #FOS: Computer and information sciences #Graph Theory and Algorithms #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.2401.14375
openalex publication_date 2024/01/25 · openalex created_date 2024/01/27 · openalex updated_date 2026/07/28
When the focus is on the relationships or interactions between entities, graphs offer an intuitive model for many real-world data. Such graphs are usually large and change over time, thus, requiring models and strategies that explore their evolution. We study the evolution of aggregated graphs and introduce the GraphTempo model that allows temporal and attribute aggregation not only on node level by grouping individual nodes, but on a pattern level as well, where subgraphs are grouped together. Furthermore, We propose an efficient strategy for exploring the evolution of the graph based on identifying time intervals of significant growth, shrinkage or stability. Finally, we evaluate the efficiency and effectiveness of the proposed approach using three real graphs.