Intelligent reasoning using general knowledge to update specific information: A database approach

Abstract

This paper describes a database framework which is similar to a relational database in style but uses alternative knowledge structures to represent uncertain data. Two knowledge structures are used, the mass assignment to represent probabilistic information and fuzzy sets to hold subjective information. We describe how the query is modified such that the selection criteria is held in the form of specific knowledge which can be updated with the more general knowledge held in the database. The updating procedure has the effect of filling in uncertain or missing information such that a final solution can be found. The operations required to perform a query are generated automatically, optimisation is performed as the operations are determined. The output from the database is in the form of a distribution over a projection of the database domain space. An example is given where a database of sea vessels can be given uncertain or noisy evidence about the characteristics of a vessel and a distribution of the likelihood of each of the vessels can be determined from the evidence.