In this paper, problems in integration of fuzzy relational databases have been investigated and some solutions have been proposed. In general, database integration consists of two main processes called schema integration and instance integration that results into global schema and global instance respectively. Current work assumes a schema integration process to get a global schema from a colle...

Fuzzy relational databases have been extensively studied in recent years, resulting in several models and constructs, some of which are implemented as software layers on top of diverse existing database systems. Fuzzy extensions to query languages and end-user query interfaces have also been developed, but the design of programming interfaces has not been properly addressed. In this paper, we d...

In our ongoing project we develop a tool which provides domain engineers with a facility to create fuzzy relational thesauri (FRT) describing subject domains. The created fuzzy relational thesauri can be used as knowledge base for an intelligent information agent when answering user queries relevant to the described domains, or for textual searching on the web. However, the manual creation of (...

The paper deals with an idea of a linguistic knowledge representation and a linguistic inference. Relational linguistic fuzzy model with weights of rules is utilising. The probability of linguistic values of antecedent and consequent variables, calculated according to Zadeh’s definition, is proposed to formulate a linguistic fuzzy model of a stochastic system. The linguistic inference procedure...

Within the framework of flexible querying of possibilistic databases, based on the fuzzy set theory, this chapter focuses on the case where the vocabulary used both in the querying language and in the data is hierarchically organized, which occurs in systems that use ontologies. We give an overview of previous works concerning two issues: firstly, flexible querying of imprecise data in the rela...

This paper pre sents a new algorithm for constructing fuzzy de cision tree s from relational database systems and gene rating fuzzy rule s from the constructed fuzzy de cision tre es. We also pre sent a me thod for dealing with the comple tene ss of the constructed fuzzy decision tree s. Based on the gene rated fuzzy rule s, we also pre sent a method for e stimating null values in re lational d...

In "Axiomatisation of fuzzy multivalued dependencies in a fuzzy relational data model" [1), Bhattacharjee and Mazumdar have introduced an extension of classical multivalued dependencies for fuzzy relational data models. The authors also proposed a set of sound and complete inference rules to derive more dependencies from a given set of fuzzy multivalued dependencies. We are afraid an important ...

The current paper presents an algorithm to build a fuzzy relational model from input-output data. The paper discuss the trade-oo between linguistic integrity and accuracy and propose an algorithm for rule extraction (AFRELI). The algorithm uses a routine named FuZion to merge consecutive membership functions and guaranteed the distinguishability between the fuzzy sets on each domain.

A key challenge for companies is to manage customer relationships as an asset. To create an effective toolkit for the analysis of customer relationships, a combination of relational databases and fuzzy logic is proposed. The fuzzy Classification Query Language allows marketers to improve customer equity, launch loyalty programs, automate mass customization, and refine marketing campaigns.

An approach to data-driven linguistic modeling is presented. The methodology is based on a fuzzy system with relational input partition that allows for transparent modeling of linear dependencies between the inputs. An identification algorithm for this type of fuzzy system is proposed. It automatically finds strongest dependencies from numerical data. An application example illustrates the usef...