RU-Topk: An Improved Algorithm of Top-k Query on Uncertain Data for Requirement Extension
The top-k query on uncertain data is required to return the first k tuples with the combination of score function and uncertainty,which is different from the tradional top-k query on deterministic data. Different users have diversified query requirements after weighing up the score and probability according to application. But the semantic of the existing top-k query on uncertain data is short of the consideration of the individuation requirement of user. To reflect the deep-seated and more accurate requirement,the concept of requirement extension degree is introduced and a top-k query semantic on uncertain data for requirement extension is defined An novel algorithm named RU-topk to process the semantic is presented The case study and the time complexity of the alrorithm are given,then it is proven that the algorithm is efficient and correct.
uncertain data query processing top-k requirement extension
Chen Ningjiang Yu Minmin Zhang Lili
College of Computer,Electronic,and Information,Guangxi University,Nanning 530004,China
国际会议
南宁
英文
5-8
2010-12-10（万方平台首次上网日期，不代表论文的发表时间）