An Efficient Algorithm for Processing Top-K Spatial Keyword Query Based on Single Quadtree Traversal

Recent years have witnessed the generation of a massive amount of spatial-textual data. In view of this, a new type of query coined spatial keyword query has been proposed to deal with the locationbased services with additional keyword constraint. This paper studies one of the most popular spatial keyword queries called Top-k Spatial Keyword Query(TkSKQ). Explicitly speaking, given a set of objects, a TkSKQ finds the k objects that are closest to the querier with each of these k objects satisfying all the keywords specified by the query. This kind of query is of paramount importance in a variety of application domains such as location-based recommendation and advertisement. The state-of-art algorithm for processing a TkSKQ is sensitive to the number of query keywords specified in the query such that its performance degrades significantly with an increase in the number of keywords. To remedy this drawback, this paper proposes a novel and simple mechanism which allows the processing time of a query to be virtually independent of the number of query keywords. Experimental results show the superiority of our proposed scheme.