A Method for Implementing a Probabilistic Model as a Relational Database
نویسندگان
چکیده
This paper discusses a method for im plementing 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 pro gramming, solving sparse linear equations, and constraint propagation. In this frame work, the probability model is represented as a generalized relational database. Subse quent probabilistic requests can be processed as standard relational queries. Conventional database management systems can be easily adopted for implementing such an approxi mate reasoning system.
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