Robust Spatio-Temporal Purchase Prediction via Deep Meta Learning

Authors

  • Huiling Qin Xidian University JD Intelligent Cities Research JD iCity, JD Technology
  • Songyu Ke Shanghai Jiao Tong University JD Intelligent Cities Research JD iCity, JD Technology
  • Xiaodu Yang Southwest Jiaotong University JD Intelligent Cities Research JD iCity, JD Technology
  • Haoran Xu Xidian University JD Intelligent Cities Research JD iCity, JD Technology
  • Xianyuan Zhan JD Intelligent Cities Research JD iCity, JD Technology
  • Yu Zheng Xidian University JD Intelligent Cities Research JD iCity, JD Technology

DOI:

https://doi.org/10.1609/aaai.v35i5.16556

Keywords:

Mining of Spatial, Temporal or Spatio-Temporal Da

Abstract

Purchase prediction is an essential task in both online and offline retail industry, especially during major shopping festivals, when strong promotion boosts consumption dramatically. It is important for merchants to forecast such surge of sales and have better preparation. This is a challenging problem, as the purchase patterns during shopping festivals are significantly different from usual cases and also rare in historical data. Most existing methods fail at this problem due to the extremely scarce data samples as well as the inability to capture the complex macroscopic spatio-temporal dependencies in a city. To address this problem, we propose the Spatio-Temporal Meta-learning Prediction (STMP) model for purchase prediction during shopping festivals. STMP is a meta-learning based spatio-temporal multi-task deep generative model. It adopts a meta-learning framework with few-shot learning capability to capture both spatial and temporal data representations. A generative component then uses the extracted spatio-temporal representation and input data to infer the prediction results. Extensive experiments demonstrate the meta-learning generalization ability of STMP. STMP outperforms baselines in all cases, which shows the effectiveness of our model.

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Published

2021-05-18

How to Cite

Qin, H., Ke, S., Yang, X., Xu, H., Zhan, X., & Zheng, Y. (2021). Robust Spatio-Temporal Purchase Prediction via Deep Meta Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 35(5), 4312-4319. https://doi.org/10.1609/aaai.v35i5.16556

Issue

Section

AAAI Technical Track on Data Mining and Knowledge Management