Predicting the structure of dynamic graphs

• URL: http://arxiv.org/abs/2401.04280v2
• Date: Thu, 25 Jul 2024 01:31:45 GMT
• Title: Predicting the structure of dynamic graphs
• Authors: Sevvandi Kandanaarachchi, Ziqi Xu, Stefan Westerlund,
• Abstract summary: We forecast the structure of a graph at future time steps incorporating unseen, new nodes and edges. We use time series forecasting methods to predict the node degree at future time points and combine these forecasts with flux balance analysis. We evaluate this approach using synthetic and real-world datasets and demonstrate its utility and applicability.
• Score: 3.035039100561926
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Many aspects of graphs have been studied in depth. However, forecasting the structure of a graph at future time steps incorporating unseen, new nodes and edges has not gained much attention. In this paper, we present such an approach. Using a time series of graphs, we forecast graphs at future time steps. We use time series forecasting methods to predict the node degree at future time points and combine these forecasts with flux balance analysis -- a linear programming method used in biochemistry -- to obtain the structure of future graphs. We evaluate this approach using synthetic and real-world datasets and demonstrate its utility and applicability.

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