The prosperity of location-based social networking services enables geo-social group queries for group-based activity planning and marketing. This paper proposes a new family of geo-social group queries with minimum acquaintance constraint (GSGQs), which are more appealing than existing geo-social group queries in terms of producing a cohesive group that guarantees the worst-case acquaintance level. GSGQs, also specified with various spatial constraints, are more complex than conventional spatial queries; particularly, those with a strict $k$NN spatial constraint are proved to be NP-hard. For efficient processing of general GSGQ queries on large location-based social networks, we devise two social-aware index structures, namely SaR-tree and SaR*-tree. The latter features a novel clustering technique that considers both spatial and social factors. Based on SaR-tree and SaR*-tree, efficient algorithms are developed to process various GSGQs. Extensive experiments on real-world Gowalla and Dianping datasets show that our proposed methods substantially outperform the baseline algorithms based on R-tree.
RISK: Efficiently processing rich spatial-keyword queries on encrypted geo-textual data
School of Artificial Intelligence, Xi’an International Studies University（西安外国语大学人工智能学院）；School of Computer Science and Technology, Xidian University（西安电子科技大学计算机科学与技术学院）；Xi’an University of Posts & Telecommunications（西安邮电大学）
GeoSQL-Eval: First Evaluation of LLMs on PostGIS-Based NL2GeoSQL Queries
State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University（武汉大学测绘遥感信息工程国家重点实验室）；School of Resource and Environmental Sciences, Wuhan University（武汉大学资源与环境科学学院）
WISK: A Workload-aware Learned Index for Spatial Keyword Queries
University of New South Wales（新南威尔士大学）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；The University of Auckland（奥克兰大学）；The University of Melbourne（墨尔本大学）；Nanyang Technological University（南洋理工大学）
From Questions to Queries: An AI-powered Multi-Agent Framework for Spatial Text-to-SQL
Geoinformation and Big Data Research Laboratory, Department of Geography, The Pennsylvania State University（宾夕法尼亚州立大学地理系地理信息与大数据研究实验室）；Institute for Computational and Data Sciences and Department of Geography, The Pennsylvania State University（宾夕法尼亚州立大学计算与数据科学研究所及地理系）
Towards Quantum Range Query for Spatial-Temporal-Semantic Trajectory Data
National University of Singapore（新加坡国立大学）；The Chinese University of Hong Kong（香港中文大学）；The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））
