Aggregate Queries for Discrete and Continuous Probabilistic XML

Sources of data uncertainty and imprecision are numerous. A way to handle this uncertainty is to associate probabilistic annotations to data. Many such probabilistic database models have been proposed, both in the relational and in the semi-structured setting. The latter is particularly well adapted to the management of uncertain data coming from a variety of automatic processes. An important problem, in the context of probabilistic XML databases, is that of answering aggregate queries (count, sum, avg, etc.), which has received limited attention so far. In a model unifying the various (discrete) semi-structured probabilistic models studied up to now, we present algorithms to compute the distribution of the aggregation values (exploiting some regularity properties of the aggregate functions) and probabilistic moments (especially, expectation and variance) of this distribution. We also prove the intractability of some of these problems and investigate approximation techniques. We final...

• Type: Conference
• Year: 2010
• Where: ICDT
• Authors: Serge Abiteboul, T.-H Hubert Chan, Evgeny Kharlamov, Werner Nutt, Pierre Senellart
• Keywords: Database, ICDT 2010