An EP-Topk Query over Uncertain Data
Zhibang Yang, Xu Zhou · 2014
The information in some applications, such as sensor networks, is inherently imprecise. The traditional techniques are unworkable to manage uncertain data efficiently and effectively. In this paper, we research one of the important data management technology, probabilistic Top-k query over uncertain data, which plays an important role in many applications including multicriteria decision making and so forth. We define the EP-Topk queries based on uncertain data model at first, and then give out a probability R-tree, which namely PR-tree, to organize the source database. We propose the EP-Topk query algorithm based on some pruning strategies finally. Extensive experiments have been conducted to verify the efficiency and the effectiveness of our algorithms with verity datasets.