2 citations · 3 across the 7 of their papers we have counts for
8 papers
Triangle Counting in Hypergraph Streams: A Complete and Practical Approach
Lingkai Meng, Long Yuan, Xuemin Lin +2
Triangle counting in hypergraph streams, including both hyper-vertex and hyper-edge triangles, is a fundamental problem in hypergraph analytics, with broad applications. However, e…
Fine-Grained Traffic Inference from Road to Lane via Spatio-Temporal Graph Node Generation
Shuhao Li, Weidong Yang, Yue Cui +4
Fine-grained traffic management and prediction are fundamental to key applications such as autonomous driving, lane change guidance, and traffic signal control. However, obtaining…
Revisiting Graph Analytics Benchmark
Lingkai Meng, Yu Shao, Long Yuan +7
The rise of graph analytics platforms has led to the development of various benchmarks for evaluating and comparing platform performance. However, existing benchmarks often fall sh…
OSS-UAgent: An Agent-based Usability Evaluation Framework for Open Source Software
Lingkai Meng, Yu Shao, Long Yuan +6
Usability evaluation is critical to the impact and adoption of open source software (OSS), yet traditional methods relying on human evaluators suffer from high costs and limited sc…
Counting Butterflies over Streaming Bipartite Graphs with Duplicate Edges
Lingkai Meng, Long Yuan, Xuemin Lin +3
Bipartite graphs are commonly used to model relationships between two distinct entities in real-world applications, such as user-product interactions, user-movie ratings and collab…
A Survey of Distributed Graph Algorithms on Massive Graphs
Lingkai Meng, Yu Shao, Long Yuan +7
Distributed processing of large-scale graph data has many practical applications and has been widely studied. In recent years, a lot of distributed graph processing frameworks and…
Unifying Lane-Level Traffic Prediction from a Graph Structural Perspective: Benchmark and Baseline
Shuhao Li, Yue Cui, Jingyi Xu +5
Traffic prediction has long been a focal and pivotal area in research, witnessing both significant strides from city-level to road-level predictions in recent years. With the advan…
High-Ratio Compression for Machine-Generated Data
Jiujing Zhang, Zhitao Shen, Shiyu Yang +7
Machine-generated data is rapidly growing and poses challenges for data-intensive systems, especially as the growth of data outpaces the growth of storage space. To cope with the s…