Abstract：To solve the problem of Topk query algorithm for widely used uncertain data without enough efficiency, a new parameterized Topk query algorithm (ETK) was proposed based on the analysis of possible world model. The data probability and the score were constrained by the algorithm, and the top k data with the highest Topk probability and the score were returned to comprehensively consider the two attributes of data probability and score. To improve the algorithm efficiency, the pruning methods were proposed based on data score, data existence probability and data dominance relationship. The proposed algorithm was compared with the previous algorithms, and the experiments were carried out for different parameters. The results show that the proposed algorithm has improved time consumption performance for dealing with uncertain data.
