Predicting the structure of dynamic graphs
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866913444302684160 |
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| author | Kandanaarachchi, Sevvandi Xu, Ziqi Westerlund, Stefan |
| author_facet | Kandanaarachchi, Sevvandi Xu, Ziqi Westerlund, Stefan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_04280 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Predicting the structure of dynamic graphs Kandanaarachchi, Sevvandi Xu, Ziqi Westerlund, Stefan Machine Learning Social and Information Networks 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. |
| title | Predicting the structure of dynamic graphs |
| topic | Machine Learning Social and Information Networks |
| url | https://arxiv.org/abs/2401.04280 |