In today's uncertain world, imprecision in probabilistic information is often specified by probability intervals. We present here a new database framework for the efficient storage and manipulation of interval probability distribution functions and their associated contextual information. While work on interval probabilities and on probabilistic databases, has appeared before, ours is the first to combine these into a coherent and mathematically sound framework including both standard relational queries and queries based on probability theory. In particular, our query algebra allows the user not only to query existing interval probability distributions, but also to construct new ones by means of conditionalization and marginalization, as well as other more common database operations.
We have designed a sister database framework for handling imprecise probabilities as represented by probability intervals, in SPOs REF .
Databases for Interval Probabilities
International Journal of Intelligent Systems
Computer Science