Abstract

AbstractSpatial keyword query plays an important role in many applications with rapid growth of spatio-textual objects collected. In this context, processing boolean spatial keyword query on road networks is one of the most interesting problems. When giving a query which contains a location and a group of keywords, our aim is to return \(k\) objects containing all the query keywords which are the nearest to the query location. Though the research on this problem has received extensive studies in Euclidean space, little is done to deal with it on road networks. We first propose novel indexing structures and algorithms that are able to process such query efficiently. Experimental results on multiple real-word datasets show that our methods achieves high performance.KeywordsRoad networksSpatial keyword searchSpatial indexing

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