Preprint version. Published in International Journal of Intelligent Systems, Volume 19, Issue 9, September 1, 2004, pages 789-815.
NOTE: At the time of publication, the author Alex Dekhtyar was not yet affiliated with Cal Poly.
The definitive version is available at https://doi.org/10.1002/int.20025.
We present a database framework for the efficient storage and manipulation of interval probability distributions and their associated information. Although 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 users 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.
This is the pre-peer reviewed version of the following article: Databases for interval probabilities, Wenzhong Zhao, Alex Dekhtyar, Judy Goldsmith, International Journal of Intelligent Systems, 19:9.