Signal propagation in complex networks

P Ji, J Ye, Y Mu, W Lin, Y Tian, C Hens, M Perc, Y Tang… - Physics reports, 2023 - Elsevier
Signal propagation in complex networks drives epidemics, is responsible for information
going viral, promotes trust and facilitates moral behavior in social groups, enables the …

Customer purchase prediction in B2C e-business: A systematic review and future research agenda

S Chen, Z Xu, D Xu, X Gou - Expert Systems with Applications, 2024 - Elsevier
Customer purchase prediction is increasingly recognized as a crucial marketing strategy in
B2C e-business, promising enhanced business profitability and customer satisfaction …

Service time prediction for delivery tasks via spatial meta-learning

S Ruan, C Long, Z Ma, J Bao, T He, R Li… - Proceedings of the 28th …, 2022 - dl.acm.org
Service time is a part of time cost in the last-mile delivery, which is the time spent on
delivering parcels at a certain location. Predicting the service time is fundamental for many …

STHAN: Transportation demand forecasting with compound spatio-temporal relationships

S Ling, Z Yu, S Cao, H Zhang, S Hu - ACM Transactions on Knowledge …, 2023 - dl.acm.org
Transportation demand forecasting is a critical precondition of optimal online transportation
dispatch, which will greatly reduce drivers' wasted mileage and customers' waiting time …

Next-point-of-interest recommendation based on joint mining of regularity and randomness

X Li, R Hu, Z Wang - Knowledge-Based Systems, 2022 - Elsevier
Abstract Point-of-interest (POI) recommendation is important in location-based applications
and has attracted considerable research interest. Despite the inspiring achievements of POI …

Successive model-agnostic meta-learning for few-shot fault time series prognosis

H Su, J Hu, S Yu, J Liu, X Qin - Neurocomputing, 2024 - Elsevier
Meta learning is a promising technique for solving few-shot fault prediction problems, which
have attracted the attention of many researchers in recent years. Existing meta-learning …

Winning tracker: a new model for real-time winning prediction in MOBA games

C Zhao, H Zhao, Y Ge, R Wu, X Shen - Proceedings of the ACM Web …, 2022 - dl.acm.org
With an increasing popularity, Multiplayer Online Battle Arena (MOBA) games where two
opposing teams compete against each other, have played a major role in E-sports …

Exploiting intra-and inter-region relations for sales prediction via graph convolutional network

Y Liu, B Guo, X Song, S Wang… - GLOBECOM 2022-2022 …, 2022 - ieeexplore.ieee.org
Region-level sales prediction is an essential task in the e-commerce industry. Accurate
demand prediction enables enterprises to respond to future sales changes in time, thereby …

DESTformer: A Transformer Based on Explicit Seasonal–Trend Decomposition for Long-Term Series Forecasting

Y Wang, J Zhu, R Kang - Applied Sciences, 2023 - mdpi.com
Seasonal–trend-decomposed transformer has empowered long-term time series forecasting
via capturing global temporal dependencies (eg, period-based dependencies) in …

MulSTE: A Multi-view Spatio-temporal Learning Framework with Heterogeneous Event Fusion for Demand-supply Prediction

L Lin, Z Lu, S Wang, Y Liu, Z Hong, H Wang… - Proceedings of the 30th …, 2024 - dl.acm.org
Recently, integrated warehouse and distribution logistics systems are widely used in E-
commerce industries to adjust to constantly changing customer demands. It makes the …