A spatial keyword evaluation framework for network-based spatial queries

Ji Zhang, Wei-Shinn Ku, Xunfei Jiang, Xiao Qin

Abstract: An increasing number of spatial keyword query techniques that return qualified objects based on a comprehensive consideration of spatial and keyword constraints have been presented in the literature. Due to the complexity of the solutions to spatial keyword queries, systems that can effectively demonstrate the mechanisms will attract interest from the spatial database research community. However, very limited visualization systems have been developed for illustrating spatial keyword query evaluation. In this demonstration, we present a system that visualizes advanced solutions to efficiently answer the Spatial Keyword k Nearest Neighbor (SKkNN) query. With the two-level data management method and the friendly user interface implemented by the Standard Widget Toolkit (SWT) and Open Graphics Library (OpenGL), our system is able to not only interact with users in diverse manners, visualize datasets, and display the SKkNN query evaluation process, but it also helps users better understand the solutions in a more intuitive way.