Spatial Query

Spatial query processing focuses on efficiently retrieving information based on location and related attributes, addressing challenges in diverse applications from map-based question answering to indoor navigation. Current research emphasizes developing novel algorithms and models, including those leveraging vision-language models, neural networks for audio-visual data integration, and machine learning for optimizing index structures and ensuring fairness in query results. These advancements aim to improve the speed, accuracy, and fairness of spatial queries across various data types and application domains, impacting fields such as location-based services, robotics, and data analysis.