Supporting various top-k queries over uncertain datasets
Wenfeng Li, Zufa Fu, Liwei Wang, Deyi Li, Zhiyong Peng · Wuhan University Journal of Natural Sciences · 2014
There have been many researches and semantics in answering top- k queries on uncertain data in various applications. However, most of these semantics must consume much of their time in computing position probability . Our approach to support various top- k queries is based on position probability distribution (PPD) sharing. In this paper, a PPD-tree structure and several basic operations on it are proposed to support various top- k queries. In addition, we proposed an approximation method to improve the efficiency of PPD generation. We also verify the effectiveness and efficiency of our approach by both theoretical analysis and experiments.