Efficient Algorithms and Cost Models for Reverse Spatial-Keyword k-Nearest Neighbor Search

摘要

Geographic objects associated with descriptive texts are becoming prevalent, justifying the need for spatial-keyword queries that consider both locations and textual descriptions of the objects. Specifically, the relevance of an object to a query is measured by spatial-textual similarity that is based on both spatial proximity and textual similarity. In this article, we introduce the Reverse Spatial-Keyword k-Nearest Neighbor (RSKkNN) query, which finds those objects that have the query as one of their As-nearest spatial-textual objects. The RSKkNN queries have numerous applications in online maps and GIS decision support systems.