Abstract
AbstractWith the increase of location-based services, Web contents are being geo-tagged, and spatial keyword queries that retrieve objects satisfying both spatial and keyword conditions are gaining in prevalence. Unfortunately, the state-of-the-art packing algorithms only focus on spatial relationship, and they are not fit for the spatial keyword queries. In this paper, we propose a new packing algorithm named KBS which takes both location and keyword information into consideration, thus optimizing R-tree for spatial keyword queries. Experimental results on both real and synthetic datasets show that our method achieves high performance and space utilization.KeywordsSpatial Keyword QueryR-treePacking Algorithm
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