25 citations · 31 across the 7 of their papers we have counts for
7 papers
GRAFT: Graph-Matched Retrieval and Fusion of Tables in Data Lakes
Daomin Ji, Hui Luo, Zhifeng Bao +2
Autonomous data agents resolve analytical queries by retrieving and reasoning over evidence in tabular data lakes. Existing methods score tables independently against the query and…
Taxonomy Maintenance In The Wild Over Evolving Scholarly Data: Reliability, Efficiency, and Cost-Effectiveness
Daomin Ji, Hui Luo, Zhifeng Bao +2
The rapid growth of scientific publications makes scholarly taxonomies quickly obsolete. We study taxonomy maintenance in the wild, a new problem that moves beyond static construct…
Table Integration in Data Lakes Unleashed: Pairwise Integrability Judgment, Integrable Set Discovery, and Multi-Tuple Conflict Resolution
Daomin Ji, Hui Luo, Zhifeng Bao +1
Table integration aims to create a comprehensive table by consolidating tuples containing relevant information. In this work, we investigate the challenge of integrating multiple t…
Dataset Discovery via Line Charts
Daomin Ji, Hui Luo, Zhifeng Bao +1
Line charts are a valuable tool for data analysis and exploration, distilling essential insights from a dataset. However, access to the underlying dataset behind a line chart is ra…
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…
Spatial Object Recommendation with Hints: When Spatial Granularity Matters
Hui Luo, Jingbo Zhou, Zhifeng Bao +5
Existing spatial object recommendation algorithms generally treat objects identically when ranking them. However, spatial objects often cover different levels of spatial granularit…
Dynamic Ridesharing in Peak Travel Periods
Hui Luo, Zhifeng Bao, Farhana M. Choudhury +1
In this paper, we study a variant of the dynamic ridesharing problem with a specific focus on peak hours: Given a set of drivers and rider requests, we aim to match drivers to each…