Consensus answers for queries over probabilistic databases (2009)
| Venue: | in PODS |
| Citations: | 9 - 1 self |
BibTeX
@INPROCEEDINGS{Li09consensusanswers,
author = {Jian Li and Amol Deshp},
title = {Consensus answers for queries over probabilistic databases},
booktitle = {in PODS},
year = {2009}
}
OpenURL
Abstract
We address the problem of finding a “best ” deterministic query answer to a query over a probabilistic database. For this purpose, we propose the notion of a consensus world (or a consensus answer) which is a deterministic world (answer) that minimizes the expected distance to the possible worlds (answers). This problem can be seen as a generalization of the well-studied inconsistent information aggregation problems (e.g. rank aggregation) to probabilistic databases. We consider this problem for various types of queries including SPJ queries, Top-k ranking queries, group-by aggregate queries, and clustering. For different distance metrics, we obtain polynomial time optimal or approximation algorithms for computing the consensus answers (or prove NP-hardness). Most of our results are for a general probabilistic database model, called and/xor tree model, which significantly generalizes previous probabilistic database models like x-tuples and block-independent disjoint models, and is of independent interest.







