Skyline Query Processing Research On Uncertain Data Set

In recent years, the uncertain data exists in many important applications, such as data mining, sensor networks, environmental monitoring, market surveillance and studies of Number in economics. In these applications, the data usually has a certain randomness and incompleteness because of the limitations of measuring equipment and the delay of data updating. Due to the importance and the accumulation of uncertain data, the task which aims at analyzing and studying a large amount of uncertain data becomes more and more significant. And the Skyline query, which is a mainly aspect of studying in uncertain data analyzing and processing, is valued by researchers in multi-objects decision studying.This paper mainly studies the Skyline query of the uncertain data set in two aspects, first it studied the control relation set of uncertain data stream query based on Skyline. This paper presents an index structure based on the relationship of the collection control, which will save dominance relationships between objects to preserve the activity period through the relationship. When dealing with the tuples that are out of date and new tuples, the new objects can be found directly by indexing the Skyline probability affected. So it can quickly update the Skyline probability. The advantage of this method is stable and the query efficiency is not affected by the uncertainty distribution of objects in space effect.Secondly,this paper also studies the uncertain data subspace Skyline query method. First it saves the full space Skyline result set which is called S, when the stator space is provided, it will carry on subspace queries in the set S, and obtain the result set Seed, then it will go back to check by the Seed tuples. The method largely resolved the problem of low efficiency of direct queries in exponential number of subspaces.