S.Krishnaveni, K.Sangeetha
In reality spatial objects (e.g., Dams) not only have spatial locations but also have quality attributes (e.g., height, reservoir capacity).Given a spatial location S, Quality vector ψ and a set of spatial objects D, a spatial query which retrieves and ranks the objects that intersect the region S and satisfies the quality vector. Based on the inverted index and the linear quad tree, we propose a novel index structure, called inverted linear quad tree (IL-Quad tree), which is carefully designed to exploit both spatial and keyword based pruning techniques to effectively reduce the search space which performs 1) spatial filtering ,2) textual filtering and 3) object ranking in a fully integrated manner. The inverted quad tree is compared with the R tree, SKR tree.