activity
20172021
most citedGlobal Context Enhanced Graph Neural Networks for Session-based Recommendation

554 citations · 645 across the 5 of their papers we have counts for

collaborators

12 papers

cs.DB202117 cited

Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation

Yuxing Han, Ziniu Wu, Peizhi Wu +11

Cardinality estimation (CardEst) plays a significant role in generating high-quality query plans for a query optimizer in DBMS. In the last decade, an increasing number of advanced…

cs.DB2021

Let Trajectories Speak Out the Traffic Bottlenecks

Hui Luo, Zhifeng Bao, Gao Cong +2

Traffic bottlenecks are a set of road segments that have an unacceptable level of traffic caused by a poor balance between road capacity and traffic volume. A huge volume of trajec…

cs.DB202172 cited

A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation

Peizhi Wu, Gao Cong

Cardinality estimation is a fundamental problem in database systems. To capture the rich joint data distributions of a relational table, most of the existing work either uses data…

cs.IR2021554 cited

Global Context Enhanced Graph Neural Networks for Session-based Recommendation

Ziyang Wang, Wei Wei, Gao Cong +3

Session-based recommendation (SBR) is a challenging task, which aims at recommending items based on anonymous behavior sequences. Almost all the existing solutions for SBR model us…

cs.DB2020

A Survey on Trajectory Data Management, Analytics, and Learning

Sheng Wang, Zhifeng Bao, J. Shane Culpepper +1

Recent advances in sensor and mobile devices have enabled an unprecedented increase in the availability and collection of urban trajectory data, thus increasing the demand for more…

cs.DB2020

Efficient and Effective Similar Subtrajectory Search with Deep Reinforcement Learning

Zheng Wang, Cheng Long, Gao Cong +1

Similar trajectory search is a fundamental problem and has been well studied over the past two decades. However, the similar subtrajectory search (SimSub) problem, aiming to return…