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The semantics of UTop-kquery is based on the possible world model, and the greatest challenge in processing UTop-kqueries is the explosion of possible world space. In this direction, several optimized algorithms have been developed. However, uncertain databases are different in data distributions under different scoring functions, which has significant influence on the performance of the existing optimizing algorithms. In this paper, we propose two novel algorithms, MSSUTop-kand quickdoi:10.1155/2015/359137 fatcat:codg2f32eves5jes6qh7zxmgzy