Efficient Processing of Top-k Queries in Uncertain Databases

Authors:
Ke Yi;Feifei Li;George Kollios;Divesh Srivastava
Affiliations:
Department of Computer Science and Engineering, Hong Kong University of Science and Technology. yike@cse.ust.hk;Department of Computer Science, Florida State University. lifeifei@cs.fsu.edu;Department of Computer Science, Boston University. gkollios@cs.bu.edu;AT&TLabs-Research. divesh@research.att.com
Venue:
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Year:
2008

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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.