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

Qiyu Liu, Libin Zheng, Lei Chen

Abstract: 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.