Query Processing in Spatial Network Databases Dimitris Papadias, Jun Zhang, Nikos Mamoulis, and Yufei Tao   View Paper (PDF)   Return to Spatial Support (Session C3) Abstract Despite the importance of spatial networks in real-life applications, most of the spatial database literature focuses on Euclidean spaces. In this paper we propose an architecture that integrates network and Euclidean information, capturing pragmatic constraints. Based on this architecture, we develop a Euclidean restriction and a network expansion framework that take advantage of location and connectivity to efficiently prune the search space. These frameworks are successfully applied to the most popular spatial queries, namely nearest neighbors, range search, closest pairs and e- distance joins, in the context of spatial network databases. ©2004 Association for Computing Machinery