Towards a Fuzzy Probabilistic Relational Data Base Model

Abstract

In the recent years, many fuzzy or probabilistic database models have been built to represent and handle imprecise or uncertain information in the real world. However, relational database models combining the relevance and strength of both fuzzy set theory and probability theory have rarely been proposed. This paper is the first step to build a fuzzy probabilistic relational data base model (FPRDB) for representing and handling vague and uncertain information. In this model, the tuple attribute value of relations is uncertain and imprecise represented by a fuzzy probabilistic triple. Using the probabilistic interpretation of relations on fuzzy sets for measuring the probability of binary relations of fuzzy set values of attributes, then, we formally define the notions of schemas, fuzzy probabilistic relations, fuzzy probabilistic functional dependencies and selection operation for FPRDB.