Top-k Query Processing in Uncertain Databases

By Mohamed A. Soliman, Ihab F. Ilyas, Kevin Chen-Chuan Chang. IEEE International Conference on Data Engineering, 2007

479 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Ranking queries on uncertain data: a probabilistic threshold approach (2008, methodology): “Our contribution. We address an application scenario other than the recent proposals in [ 26 , 22].”
Efficient Top-k Query Evaluation on Probabilistic Data (2007, background): “Recent work [19], handles the problem of computing Top-K queries when the uncertain data is specified by “generation rules”, in our case the complexity from the complexity of queries over the uncertain data.”
A survey of top-k query processing techniques in relational database systems (2008, methodology): “Processing framework for uncertain top-k processing [Soliman et al. 2007].”
A Survey of Uncertain Data Algorithms and Applications (2009, methodology): “One key result presented in [74] is that among all sequential access methods, the retrieval of tuples in the order of their scores leads to the least possible number of accessed tuples to answer uncertain top-k queries.”
Probabilistic frequent itemset mining in uncertain databases (2009, methodology): “Probabilistic top-k query approaches [14, 17, 12] are usually associated with uncertain databases using the tuple uncertainty model.”