Query on uncertain data has received much attention in recent years, especially with the development of Location-based services（LBS）. Little research is focused on reverse k nearest neighbor queries on uncertain data. We study the Probabilistic reverse k nearest neighbor（PRkN N） queries on uncertain data. It is succinctly shown that, PRkN N query retrieves all the points that have higher probabilities than a given threshold value to be the Reverse k-nearest neighbor（RkN N） of query data Q.The previous works on this topic mostly process with k ＞ 1.Some algorithms allow the cases for k ＞ 1, but the efficiency is inefficient especially for large k. We propose an efficient pruning algorithm — Spatial pruning heuristic with louer and upper bound（SPHLU） for solving the PRkN N queries for k ＞ 1. The experimental results demonstrate that our algorithm is even more efficient than the existent algorithms especial for a large value of k.
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