- Keywords: probabilistic databases
- TL;DR: We propose adding constraints to open-world probabilistic databases
- Abstract: Increasing amounts of available data have led to a heightened need for useful waysof representing large-scale probabilistic knowledge bases. One such approach is to use aprobabilistic database, a model with strong assumptions that allow for efficiently answeringmany interesting queries. Recent work on open-world probabilistic databases strengthensthe semantics of these probabilistic databases by discarding the assumption that any in-formation not present in the data must be false. In this paper we build upon open-worldprobabilistic databases, strengthening the semantics further by using constraints to restrictthis open world in a reasonable way. We establish a basic hardness result subject to theseconstraints, showing that the addition of constraints causes a fundamental change in thedifficulty of query evaluation and opening an interesting new theoretical direction. Finally, we propose an efficient approximation for a large class of interesting queries, providingbounds with their guaranteed tightness.
- Archival status: Non-Archival
- Subject areas: Databases, Reasoning