This book presents the advancements and applications of neutrosophics, which are
generalizations of fuzzy logic, fuzzy set, and imprecise probability. The neutrosophic logic …

In an uncertain database, every object o is associated with a probability density function,
which describes the likelihood that o appears at each position in a multidimensional …

This paper describes a generalization of the relational model in order to capture and
manipulate a type of probabilistic information. Probabilistic databases are formalized by …

This chapter will present the use of fuzzy set theory in databases. Particular emphasis is on
the relational data model and possibility and similarity based approaches to representation …

Abstract Information Source Tracking (IST) method has been developed recently for the
modeling and manipulation of uncertain and inaccurate data in relational databases. In this …

In this paper we deal with the problem of treating with dependencies in relational databases
which do not hold in an exact manner as classical functional dependencies but in a weaker …

The queries on type-2 fuzzy relational databases may get non-reasonable answers, and as
pointed out by Buckles, a tuple's membership value is not static but is a measure of the …

An important reality when studying relational databases is the fact that entries in relational
tables may often be “missing” or only partially specified. The study of such missing …

This is an evolving bibliography of documents on uncertainty and imprecision in information
systems. By uncertainty and imprecision, we mean the representation of and query support …

While incomplete information is endemic to real-world data, current multidimensional data
models are not engineered to manage incomplete information in base data, derived data …