Computing Subspace Skylines without Dominance Tests Using Set Interaction Approaches

Now a day’s preference answering plays major role in all crucial applications. If user wants to find top k–objects from a set of high dimensional data based on any monotonic function requires huge computation. One of the promising methods to compute preference set is <em>Skyline Technology.</em> Sky line computation returns the set objects that are not overruled by any other objects in n a multi dimensional space. If data is high dimensional, different users requests sky line set based on different dimensions. It requires subspace skyline computation. If objects are d-dimensional we need to compute skyline sets in 2ddifferent subspaces, called as SKYLINE CUBE computation, which incurs lot of computation cost. In this paper we address the problem of finding subspace skyline computation with minimum effort by using simple set interaction methods. By that we can decrease the number of subspace skylines need to be searched to find full sky cube. In this paper we developed one algorithm which uses Boolean algebra rules, skyline lattice to reduce dominance test for preparing sub space skylines.