Title: A method for implementing a probabilistic model as a relational database
Abstract: This paper discusses a method for implementing a probabilistic inference system based on an extended relational data model. This model provides a unified approach for a variety of applications such as dynamic programming, solving sparse linear equations, and constraint propagation. In this framework, the probability model is represented as a generalized relational database. Subsequent probabilistic requests can be processed as standard relational queries. Conventional database management systems can be easily adopted for implementing such an approximate reasoning system.
Publication Year: 1995
Publication Date: 1995-08-18
Language: en
Type: article
Access and Citation
Cited By Count: 51
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