Mapping Fuzzy EER Model Concepts to Relations

Mapping Fuzzy EER Model Concepts to Relations

Jose Galindo (Universidad de Málaga, Spain), Angelica Urrutia (Universidad Católica del Maule, Chile) and Mario Piattini (Universidad de Castilla-La Mancha, Spain)
Copyright: © 2006 |Pages: 8
DOI: 10.4018/978-1-59140-324-1.ch006
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Abstract

This chapter shows the transformation of the FuzzyEER model to a logical design by using relational databases. The FuzzyEER-to-Relational mapping algorithm is based on the “classical” EER-to-Relational mapping algorithm, published in Elmasri and Navathe (2000) and summarized in the first section of this chapter, but other versions are very similar (De Miguel, Piattini, & Marcos, 1999; Silverschatz, Korth, & Sudarshan, 2002). The FuzzyEER-to-Relational mapping algorithm includes additional rules for mapping fuzzy concepts. The following sections translate the FuzzyEER concepts, that is, the definitions in Chapter IV, to the FIRST-2 schema, which was exposed in Chapter V. Thus, this chapter relates Chapter IV with Chapter V, obtaining a fuzzy relational database. In addition, we need a comprehensive fuzzy database language with statements for data definition, query, and update. This language is FSQL (Fuzzy SQL), and we describe it in Chapter VII.

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Dedication
José Galindo, Angelica Urrutia , Mario Piattini
Table of Contents
Foreword
Juan M. Medina
Preface
Leoncio Jiménez
Acknowledgments
Chapter 1
Jose Galindo, Angelica Urrutia, Mario Piattini
This book mixes concepts of different areas of knowledge or technologies, such as databases, system architecture design, SQL language, programming... Sample PDF
Introduction to Fuzzy Logic
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Chapter 2
Jose Galindo, Angelica Urrutia, Mario Piattini
Both the problem of representation and the treatment of imprecise information have been widely discussed. Many references can be found in the... Sample PDF
Fuzzy Database Approaches
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Chapter 3
Jose Galindo, Angelica Urrutia, Mario Piattini
On occasion, the term imprecision embraces several meanings that we should differentiate. For example, as you saw in Chapter II, the information you... Sample PDF
State of the Art in Fuzzy Database Modeling
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Chapter 4
Jose Galindo, Angelica Urrutia, Mario Piattini
In this chapter we present the FuzzyEER Model, which is an extension of the EER Model with fuzzy semantics and notations. The Entity-Relationship... Sample PDF
FuzzyEER: Main Characteristics of a Fuzzy Conceptual Modeling Tool
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Chapter 5
Jose Galindo, Angelica Urrutia, Mario Piattini
The Relational Model was developed by E.F. Codd of IBM and published in 1970. It is currently the most used and has been a milestone in the history... Sample PDF
Representation of Fuzzy Knowledge in Relational Databases: FIRST-2
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Chapter 6
Jose Galindo, Angelica Urrutia, Mario Piattini
This chapter shows the transformation of the FuzzyEER model to a logical design by using relational databases. The FuzzyEER-to-Relational mapping... Sample PDF
Mapping Fuzzy EER Model Concepts to Relations
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Chapter 7
Jose Galindo, Angelica Urrutia, Mario Piattini
The SQL language was essentially developed by Chamberlin and Boyce (1974) and Chamberlin et al. (1976). In 1986, the American National Standard... Sample PDF
FSQL: A Fuzzy SQL for Fuzzy Databases
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Chapter 8
Jose Galindo, Angelica Urrutia, Mario Piattini
The applications of databases are immense. In almost all of them, the advantages of the fuzzy databases can be applied, exploiting their innovative... Sample PDF
Some Applications of Fuzzy Databases With FSQL
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Chapter 9
Jose Galindo, Angelica Urrutia, Mario Piattini
Fuzzy logic (Chapter I) allows us to bring the operation of information systems closer to the working methods of humans. People frequently deal with... Sample PDF
Brief Summary and Future Trends
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Summary of FuzzyEER Model
FRDB Architecture: The FSQL Server
Acronyms and the Greek Alphabet
About the Authors