activity
20132022
most citedDetectorNet: Transformer-enhanced Spatial Temporal Graph Neural Network for Traffic Prediction

19 citations · 19 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2022

Random Ensemble Reinforcement Learning for Traffic Signal Control

Ruijie Qi, Jianbin Huang, He Li +3

Traffic signal control is a significant part of the construction of intelligent transportation. An efficient traffic signal control strategy can reduce traffic congestion, improve…

cs.CV202119 cited

DetectorNet: Transformer-enhanced Spatial Temporal Graph Neural Network for Traffic Prediction

He Li, Shiyu Zhang, Xuejiao Li +6

Detectors with high coverage have direct and far-reaching benefits for road users in route planning and avoiding traffic congestion, but utilizing these data presents unique challe…

cs.IR2020

Association Rules Enhanced Knowledge Graph Attention Network

Zhenghao Zhang, Jianbin Huang, Qinglin Tan

Most existing knowledge graphs suffer from incompleteness. Embedding knowledge graphs into continuous vector spaces has recently attracted increasing interest in knowledge base com…

cs.SI2020

Multi-View Dynamic Heterogeneous Information Network Embedding

Zhenghao Zhang, Jianbin Huang, Qinglin Tan

Most existing Heterogeneous Information Network (HIN) embedding methods focus on static environments while neglecting the evolving characteristic of realworld networks. Although se…

cs.DB2018

A Semantic-Rich Similarity Measure in Heterogeneous Information Networks

Yu Zhou, Jianbin Huang, Heli Sun

Measuring the similarities between objects in information networks has fundamental importance in recommendation systems, clustering and web search. The existing metrics depend on t…

cs.DS2013

Backward Path Growth for Efficient Mobile Sequential Recommendation

Jianbin Huang, Xuejun Huangfu, Heli Sun +2

The problem of mobile sequential recommendation is presented to suggest a route connecting some pick-up points for a taxi driver so that he/she is more likely to get passengers wit…