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E-commerce has gone a long way in empowering merchants through the internet.In order to store the goods efficiently and arrange the marketing resourceproperly, it is important for them to make the accurate gross merchandise value(GMV) prediction. However, it's nontrivial to make accurate prediction with thedeficiency of digitized data. In this article, we present a solution to betterforecast GMV inside Alipay app. Thanks to graph neural networks (GNN) which hasgreat ability to correlate different entities to enrich information, we proposeGaia, a graph neural network (GNN) model with temporal shift aware attention.Gaia leverages the relevant e-seller' sales information and learn neighborcorrelation based on temporal dependencies. By testing on Alipay's real datasetand comparing with other baselines, Gaia has shown the best performance. AndGaia is deployed in the simulated online environment, which also achieves greatimprovement compared with baselines.

Gaia: Graph Neural Network with Temporal Shift aware Attention for Gross Merchandise Value Forecast in E-commerce