SUBSTITUTION: An efficient algorithm for probability skyline queries on discrete uncertain data

In the practical work, uncertain data are very important data type in a lot of applications. The ability to deal with uncertain data is becoming increasingly important for modern database applications. Meanwhile, there is an important analysis technique for certain data named skyline operator which finds the good solution in multidimensional environment. In this paper, the skyline query was introduced into the field of uncertain data, and the skyline queries for discrete uncertain data probability were in-depth studied. This paper researched the instance of discrete uncertain data object, and putted forward a new algorithm for inquires the p-skyline (the object set that object´s skyline probability is greater than the threshold p). The algorithm determine whether the uncertain object in the p-skyline set through the way which divide a uncertain object´s instance set into several smaller sets, at the same time, and analysis objects use the lower and upper probability bound of skyline. In the experiment section, an extensive experimental evaluation demonstrates both the effectiveness and the efficiency of our technique which choose a part of the real data for NBA player.