Spatial database keyword search is very useful in many real-time applications. Traditional m closest keyword algorithm is not scalable for very large datasets and moreover, existing algorithms are mainly based on inter-object distances only. This paper aimed to develop a process that can do the best keyword search. It is also aimed to develop an algorithm to improve scalability in terms of both inter-object distance and rating of objects. The present study proposes a method of finding spatial object groups according to the spatial query imposed. The results proved that the proposed three-dimensional keyword search process can provide better efficiency in terms of accuracy and optimum results.
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