Uncertain Dynamic Skyline Queries for Uncertain Databases

In this paper, we research the relationship between the probabilistic products and customer preferences, which has not been studied before. In order to find out products which can meet a customer's maximum demand, we present an uncertain dynamic skyline (UDS) query, and propose effective pruning strategies to reduce the search space of the UDS query processing. In addition, effective algorithms are presented by integrating the proposed pruning strategies. Extensive experiments illustrate the efficiency and effectiveness of our proposed algorithms with a variety of experiments settings.