Abstract: The semantic of the existing top-k query on uncertain data only returns one response, which has the largest gathered probability in all possible worlds. As a result, it cannot meet the consideration of users' individuation requirement. To address this issue, the concept of requirement extend degree was introduced and a top-k query semantic on uncertain data for requirement extension was defined. Further, an algorithm named RU-Topk to process the semantic was presented. The Experimental results show the superiority of RU-Topk algorithm in terms of run time for per query ansaver and query efficiency compared with the existing algorithms under the condition of meeting users'requirements.

Key words: Ucertainty data,hop-k,Requirement extension