SemSTG: Semantic State Transition Graphs for Time Series Event Forecasting
This paper constructs a semantic state transition graph (SemSTG) from time series with a self-supervised state recognition approach, and introduces a novel graph neural network to learn robust representations of the semantic state transition graph.
Jie Zhang, Peng Wang, Wei Wang
· Proceedings of the 35th ACM... · 0 citations