Abstract
With the rapid development of GPS-enabled devices, spatial keyword query, considering both spatial proximity to a query location and the textual relevance to the query keywords, is applied to many real-world applications. In this context, we study a specific type of spatial keyword query Textual-restricted K Spatial Keyword query (TK-SK query), which returns the nearest \(k\) points of interest (POIs) whose textual description is not less than a specified textual relevance threshold and whose location is close to the query location. We further propose a baseline approach and two advanced approaches (a separated index approach and a hybrid index approach) with different indexing strategies to solve this problem. Our comprehensive experiments conducted on real spatial datasets clearly demonstrate the efficiency of our two advanced approaches.
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