Efficient Processing of Top-k Queries in Uncertain Databases

Abstract

This work introduces novel polynomial-time algorithms for processing top-k: queries in uncertain databases, under the generally adopted model of x-relations. An x-relation consists of a number of x-tuples, and each x-tuple randomly instantiates Into one tuple from one or more alternatives. Our results significantly improve the best known algorithms for top-k query processing in uncertain databases, In terms of both running time and memory usage. Focusing on the single-alternative case, the new algorithms are orders of magnitude faster.