110 citations · 146 across the 7 of their papers we have counts for
7 papers
Friend Ranking in Online Games via Pre-training Edge Transformers
Liang Yao, Jiazhen Peng, Shenggong Ji +4
Friend recall is an important way to improve Daily Active Users (DAU) in online games. The problem is to generate a proper lost friend ranking list essentially. Traditional friend…
Spatio-Temporal Dynamic Graph Relation Learning for Urban Metro Flow Prediction
Peng Xie, Minbo Ma, Tianrui Li +4
Urban metro flow prediction is of great value for metro operation scheduling, passenger flow management and personal travel planning. However, it faces two main challenges. First,…
HiSTGNN: Hierarchical Spatio-temporal Graph Neural Networks for Weather Forecasting
Minbo Ma, Peng Xie, Fei Teng +4
Weather Forecasting is an attractive challengeable task due to its influence on human life and complexity in atmospheric motion. Supported by massive historical observed time serie…
ScaleVLAD: Improving Multimodal Sentiment Analysis via Multi-Scale Fusion of Locally Descriptors
Huaishao Luo, Lei Ji, Yanyong Huang +3
Fusion technique is a key research topic in multimodal sentiment analysis. The recent attention-based fusion demonstrates advances over simple operation-based fusion. However, thes…
Local structure can identify and quantify influential global spreaders in large scale social networks
Yanqing Hu, Shenggong Ji, Yuliang Jin +3
Measuring and optimizing the influence of nodes in big-data online social networks are important for many practical applications, such as the viral marketing and the adoption of ne…
Effective spreading from multiple leaders identified by percolation in social networks
Shenggong Ji, Linyuan Lu, Chi Ho Yeung +1
Social networks constitute a new platform for information propagation, but its success is crucially dependent on the choice of spreaders who initiate the spreading of information.…
Multiple Hybrid Phase Transition: Bootstrap Percolation on Complex Networks with Communities
Chong Wu, Shenggong Ji, Rui Zhang +4
Bootstrap percolation is a well-known model to study the spreading of rumors, new products or innovations on social networks. The empirical studies show that community structure is…