Computer Science – Databases
Scientific paper
2008-11-14
Computer Science
Databases
60 pages, section 4.4 added, section 6 added, typos corrected
Scientific paper
We study here fundamental issues involved in top-k query evaluation in probabilistic databases. We consider simple probabilistic databases in which probabilities are associated with individual tuples, and general probabilistic databases in which, additionally, exclusivity relationships between tuples can be represented. In contrast to other recent research in this area, we do not limit ourselves to injective scoring functions. We formulate three intuitive postulates that the semantics of top-k queries in probabilistic databases should satisfy, and introduce a new semantics, Global-Topk, that satisfies those postulates to a large degree. We also show how to evaluate queries under the Global-Topk semantics. For simple databases we design dynamic-programming based algorithms, and for general databases we show polynomial-time reductions to the simple cases. For example, we demonstrate that for a fixed k the time complexity of top-k query evaluation is as low as linear, under the assumption that probabilistic databases are simple and scoring functions are injective.
Chomicki Jan
Zhang Xi
No associations
LandOfFree
Semantics and Evaluation of Top-k Queries in Probabilistic Databases does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Semantics and Evaluation of Top-k Queries in Probabilistic Databases, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Semantics and Evaluation of Top-k Queries in Probabilistic Databases will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-10634