RIDE: A System for Generalized Region of Interest Discovery and Exploration

As an important operator for spatial data analytics, Region of Interest (ROI) query is of great importance in many location-based services such as event detection, location recommendation and smart transportation. To address the challenge of conducting ROI queries on the increasingly complex spatial...

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Bibliographic Details
Published in2020 IEEE 36th International Conference on Data Engineering (ICDE) pp. 1738 - 1741
Main Authors Liu, Qiyu, Zheng, Libin, Chen, Lei
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2020
Subjects
Big Spatial Analytics
Geometry
Indexing
Query processing
Region Exploration
ROI Queries
Spatial databases
Structured Query Language
User interfaces
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Summary:As an important operator for spatial data analytics, Region of Interest (ROI) query is of great importance in many location-based services such as event detection, location recommendation and smart transportation. To address the challenge of conducting ROI queries on the increasingly complex spatial data, we present RIDE, an efficient and effective system for generalized ROI Discovery and Exploration. Different from existing studies and systems, RIDE supports a large spectrum of region score functions and query geometries, enabling customized ROI queries for different application scenarios. This demonstration proposal introduces the basic concept of ROI queries and key components of the RIDE system, including data storage and indexing, ROI query processing and optimization and user interface.
ISSN:2375-026X
DOI:10.1109/ICDE48307.2020.00158