Paper Title
K-Nearest Neighbours Approximate Keyword Search for Spatial Database

Abstract
Keyword search over a large amount of data is an important operation in a wide range of domains. Nearest neighbor objects with required for location-based search from spatial database has been well studied for years due to its importance to commercial search engines. Specially, the top-k 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, inconsistencies and errors can exist in the user�s typed queries. This paper proposes new index structure that combines K-d tree and inverted file to answer such query efficiently and we also discuss how to answer the queries that contain the user typing error in keyword. Keywords- KNN Approximate Keyword Search, Experimental Results.