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 cant 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 unproved 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.
Junchang Xin Mei Bai Guoren Wang
Key Laboratory of Medical Image Computing (Northeastern University), Ministry of Education, China Co College of Information Science and Engineering, Northeastern University, China
国际会议
2011 Seventh International Conference on Natural Computation(第七届自然计算国际会议 ICNC 2011)
上海
英文
321-325
2011-07-26（万方平台首次上网日期，不代表论文的发表时间）