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Top-k query processing in probabilistic databases with non-materialized views
2013
2013 IEEE 29th International Conference on Data Engineering (ICDE)
We investigate a novel approach of computing confidence bounds for top-k ranking queries in probabilistic databases with non-materialized views. Unlike related approaches, we present an exact pruning algorithm for finding the topranked query answers according to their marginal probabilities without the need to first materialize all answer candidates via the views. Specifically, we consider conjunctive queries over multiple levels of select-project-join views, the latter of which are cast into
doi:10.1109/icde.2013.6544819
dblp:conf/icde/DyllaMT13
fatcat:pw37hkukv5fnndzpoyeklbi4va