A Demonstration of QARTA: An ML-based System for Accurate Map Services [conference paper]
Conference
47th International Conference on Very Large Data Bases (VLDB 2021) - August 16-20, 2021
Authors
Sofiane Abbar, Rade Stanojevic, Mashaal Musleh (Ph.D. student), Mohamed ElShrif, Mohamed Mokbel (professor)
Abstract
This demo presents QARTA; an open-source full-fledged system for highly accurate and scalable map services. QARTA employs machine learning techniques to:(a) construct its own highly accurate map in terms of both map topology and edge weights, and (b) calibrate its query answers based on contextual information, including transportation modality, underlying algorithm, and time of day/week. The demo is based on actual deployment of QARTA in all Taxis in the State of Qatar and in the third-largest food delivery company in the country, and receiving hundreds of thousands of daily API calls with a real-time response time. Audience will be able to interact with the demo through various scenarios that show QARTA map and query accuracy as well as internals of QARTA.
Link to full paper
A Demonstration of QARTA: An ML-based System for Accurate Map Services
Keywords
databases, spatial computing, machine learning