Efficient threshold skyline query processing in uncertain databases

With the development of human knowledge, the uncertainty of data, widely existing in computer applications, has got more attentions from researchers and the research of it becomes a hot topic. Because of the probability, traditional skyline queries algorithms can´t be used in uncertain databases. In this paper, firstly, we introduce the concepts of skyline probability and threshold skyline. Then we propose two query algorithms in uncertain databases, threshold skyline query without rules and threshold skyline query with rules. Basic p-Skyline algorithm (BPS) and improved p-Skyline algorithm (IPS) can calculate the p-Skyline when there are no rules in tuples, and IPS which add some filters is the amelioration of BPS. Rule probability calculation algorithm (RPC) can calculate the probability of rule when there are rules in the tuples. In this paper, we consider two rules: mutually exclusive rule and coexistence rule. The mutually exclusive rule means that at most one tuple in the rule can exist in one possible world. The coexistence exclusive rule means that all the tuples in the rule must appear in one possible world at the same time. At last, through a large number of experiments, all algorithms are proved correct and effective.