Index Structure for Nearest Neighbors Search with Required Keywords on Spatial Database

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There is more and more commercial and research interest in nearest neighbor objects for location-based search from spatial database. Specially, a spatial keyword query takes a user location and user-supplied keywords as arguments and returns objects that is nearest k objects from user current location and textually relevant to the user required keyword. In these systems, user can type one or more word for required keyword. To find the result that contains at least one required keyword, it is important to support Boolean OR semantic keyword search on spatial database. In this paper we study how to answer such queries efficiently for both kNN query and range query. This paper proposes new index structure that combines K-d tree and inverted file. K-d tree efficiently support for both nearest neighbor and range queries. We also discuss Boolean OR Semantic keyword search for the user’s required keywords.