554 citations · 910 across the 20 of their papers we have counts for
20 papers
On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence
Gengchen Mai, Weiming Huang, Jin Sun +11
Large pre-trained models, also known as foundation models (FMs), are trained in a task-agnostic manner on large-scale data and can be adapted to a wide range of downstream tasks by…
WISK: A Workload-aware Learned Index for Spatial Keyword Queries
Yufan Sheng, Xin Cao, Yixiang Fang +4
Spatial objects often come with textual information, such as Points of Interest (POIs) with their descriptions, which are referred to as geo-textual data. To retrieve such data, sp…
Improving the Inference of Topic Models via Infinite Latent State Replications
Daniel Rugeles, Zhen Hai, Juan Felipe Carmona +2
In text mining, topic models are a type of probabilistic generative models for inferring latent semantic topics from text corpus. One of the most popular inference approaches to to…
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…
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…
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…
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…
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…
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…
Interaction-aware Kalman Neural Networks for Trajectory Prediction
Ce Ju, Zheng Wang, Cheng Long +2
Forecasting the motion of surrounding obstacles (vehicles, bicycles, pedestrians and etc.) benefits the on-road motion planning for intelligent and autonomous vehicles. Complex sce…
Representation Learning for Spatial Graphs
Zheng Wang, Ce Ju, Gao Cong +1
Recently, the topic of graph representation learning has received plenty of attention. Existing approaches usually focus on structural properties only and thus they are not suffici…
HyperML: A Boosting Metric Learning Approach in Hyperbolic Space for Recommender Systems
Lucas Vinh Tran, Yi Tay, Shuai Zhang +2
This paper investigates the notion of learning user and item representations in non-Euclidean space. Specifically, we study the connection between metric learning in hyperbolic spa…
Interact and Decide: Medley of Sub-Attention Networks for Effective Group Recommendation
Lucas Vinh Tran, Tuan-Anh Nguyen Pham, Yi Tay +3
This paper proposes Medley of Sub-Attention Networks (MoSAN), a new novel neural architecture for the group recommendation task. Group-level recommendation is known to be a challen…
Heron Inference for Bayesian Graphical Models
Daniel Rugeles, Zhen Hai, Gao Cong +1
Bayesian graphical models have been shown to be a powerful tool for discovering uncertainty and causal structure from real-world data in many application fields. Current inference…
SURGE: Continuous Detection of Bursty Regions Over a Stream of Spatial Objects
Kaiyu Feng, Tao Guo, Gao Cong +2
With the proliferation of mobile devices and location-based services, continuous generation of massive volume of streaming spatial objects (i.e., geo-tagged data) opens up new oppo…
Reverse k Nearest Neighbor Search over Trajectories
Sheng Wang, Zhifeng Bao, J. Shane Culpepper +2
GPS enables mobile devices to continuously provide new opportunities to improve our daily lives. For example, the data collected in applications created by Uber or Public Transport…
Distributed Publish/Subscribe Query Processing on the Spatio-Textual Data Stream
Zhida Chen, Gao Cong, Zhenjie Zhang +2
Huge amount of data with both space and text information, e.g., geo-tagged tweets, is flooding on the Internet. Such spatio-textual data stream contains valuable information for mi…
Keyword-aware Optimal Route Search
Xin Cao, Lisi Chen, Gao Cong +1
Identifying a preferable route is an important problem that finds applications in map services. When a user plans a trip within a city, the user may want to find "a most popular ro…
Efficient Spatial Keyword Search in Trajectory Databases
Gao Cong, Hua Lu, Beng Chin Ooi +2
An increasing amount of trajectory data is being annotated with text descriptions to better capture the semantics associated with locations. The fusion of spatial locations and tex…
Shortest Path and Distance Queries on Road Networks: An Experimental Evaluation
Lingkun Wu, Xiaokui Xiao, Dingxiong Deng +3
Computing the shortest path between two given locations in a road network is an important problem that finds applications in various map services and commercial navigation products…