Introduction to spatio-temporal data driven urban computing

This special issue of Distributed and Parallel Databases journal covers recent advances in spatio-temporal data analytics in the context of urban computing. It contains 9 articles that present solid research studies and innovative ideas in the area of spatio-temporal data analytics for urban computing applications. All of the 9 papers went through at least two rounds of rigorous reviews by the guest editors and invited reviewers. Location-based recommender systems are becoming increasingly important in the community of urban computing. The paper, by Hao Zhou et al., “Hybrid route recommendation with taxi and shared bicycles,” develops a two-phase data-driven recommendation framework that integrates prediction and recommendation phases for providing reliable route recommendation results. Another paper, by Hao Zhang et al., “On accurate POI recommendation via transfer learning,” proposes a transfer learning based deep neural model that fuses cross-domain knowledge to achieve more accurate POI recommendation. Spatial keyword search has been receiving much attention in area of spatio-temporal data analytics. Xiangguo Zhao et al. develop anindex structure that comprehensively considers the social, spatial, and textual information of massive-scale spatio-temporal data to support social-aware spatial keyword group query in their paper “Social-aware spatial keyword top-k group query.” Jiajie Xu et al. propose a hybrid indexing structure that integrate the spatial and semantic information of spatio-temporal datain their paper “Multi-objective spatial keyword query with semantics: a distance-owner based approach.” Matching of spatio-temporal data is a fundamental research problem in spatiotemporal data analytics. The paper, by Ning Wang et al., “An efficient algorithm for spatio-textual location matching,” targets the problem of finding all location pairs whose spatio-textual similarity exceeds a given threshold. This matching query is useful in urban computing applications including hot region detection and traffic