4.4 Article Proceedings Paper

A Demonstration of QARTA: An ML-based System for Accurate Map Services

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Editorial Material Computer Science, Hardware & Architecture

Traffic Routing in the Ever -Changing City of Doha

Sofiane Abbar et al.

COMMUNICATIONS OF THE ACM (2021)

Article Computer Science, Information Systems

QARTA: An ML-based System for Accurate Map Services

Mashaal Musleh et al.

Summary: This study presents QARTA, an open-source system for highly accurate and scalable map services that constructs its own accurate map using machine learning techniques and calibrates query answers based on contextual information.

PROCEEDINGS OF THE VLDB ENDOWMENT (2021)

Article Computer Science, Information Systems

DeepTRANS: A Deep Learning System for Public Bus Travel Time Estimation using Traffic Forecasting

Luan Tran et al.

PROCEEDINGS OF THE VLDB ENDOWMENT (2020)

Article Computer Science, Information Systems

Efficient Shortest Path Index Maintenance on Dynamic Road Networks with Theoretical Guarantees

Dian Ouyang et al.

PROCEEDINGS OF THE VLDB ENDOWMENT (2020)

Article Computer Science, Information Systems

Machine Learning Meets Big Spatial Data

Ibrahim Sabek et al.

PROCEEDINGS OF THE VLDB ENDOWMENT (2019)

Article Computer Science, Information Systems

Querying Shortest Paths on Time Dependent Road Networks

Yong Wang et al.

PROCEEDINGS OF THE VLDB ENDOWMENT (2019)

Proceedings Paper Computer Science, Information Systems

RoadRunner: Improving the Precision of Road Network Inference from GPS Trajectories

Songtao He et al.

26TH ACM SIGSPATIAL INTERNATIONAL CONFERENCE ON ADVANCES IN GEOGRAPHIC INFORMATION SYSTEMS (ACM SIGSPATIAL GIS 2018) (2018)

Proceedings Paper Computer Science, Interdisciplinary Applications

Road Network Fusion for Incremental Map Updates

Rade Stanojevic et al.

PROGRESS IN LOCATION BASED SERVICES 2018 (2018)

Article Computer Science, Information Systems

Shortest Path and Distance Queries on Road Networks: An Experimental Evaluation

Lingkun Wu et al.

PROCEEDINGS OF THE VLDB ENDOWMENT (2012)