Semantics and Evaluation of Top-k Queries in Probabilistic Databases - Computer Science > DatabasesReport as inadecuate




Semantics and Evaluation of Top-k Queries in Probabilistic Databases - Computer Science > Databases - Download this document for free, or read online. Document in PDF available to download.

Abstract: We study here fundamental issues involved in top-k query evaluation inprobabilistic databases. We consider simple probabilistic databases in whichprobabilities are associated with individual tuples, and general probabilisticdatabases in which, additionally, exclusivity relationships between tuples canbe represented. In contrast to other recent research in this area, we do notlimit ourselves to injective scoring functions. We formulate three intuitivepostulates that the semantics of top-k queries in probabilistic databasesshould satisfy, and introduce a new semantics, Global-Topk, that satisfiesthose postulates to a large degree. We also show how to evaluate queries underthe Global-Topk semantics. For simple databases we design dynamic-programmingbased algorithms, and for general databases we show polynomial-time reductionsto the simple cases. For example, we demonstrate that for a fixed k the timecomplexity of top-k query evaluation is as low as linear, under the assumptionthat probabilistic databases are simple and scoring functions are injective.



Author: Xi Zhang, Jan Chomicki

Source: https://arxiv.org/







Related documents