4 papers
Efficient Prompt Learning for Traffic Forecasting
Qianru Zhang, Xinyi Gao, Alexander Zhou +3
Accurate traffic prediction is essential for optimizing transportation systems, enhancing resource allocation, and improving overall urban administration. Spatio-temporal graph neu…
Efficient and Effective Table-Centric Table Union Search in Data Lakes
Yongkang Sun, Zhihao Ding, Huiqiang Wang +2
In data lakes, information on the same subject is often fragmented across multiple tables. Table union search aims to find the top-k tables that can be unioned with a query table t…
Multi-granularity Spatiotemporal Flow Patterns
Chrysanthi Kosyfaki, Nikos Mamoulis, Reynold Cheng +1
Analyzing flow of objects or data at different granularities of space and time can unveil interesting insights or trends. For example, transportation companies, by aggregating pass…
A Sampling-based Framework for Hypothesis Testing on Large Attributed Graphs
Yun Wang, Chrysanthi Kosyfaki, Sihem Amer-Yahia +1
Hypothesis testing is a statistical method used to draw conclusions about populations from sample data, typically represented in tables. With the prevalence of graph representation…