Representation of Fuzzy Knowledge in Relational Databases

2006 ◽  
pp. 145-170
Author(s):  
Jose Galindo ◽  
Angelica Urrutia ◽  
Mario Piattini
Keyword(s):  
Fuzzy Logic ◽  
Relational Database ◽  
Relational Databases ◽  
Relational Model ◽  
Uncertain Information ◽  
Theoretical Level ◽  
Database Models ◽  
History Of ◽  
Fuzzy Knowledge

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 of databases, revolutionizing the market. In fact, relational databases have been the most widespread of all databases. On a theoretical level, many Fuzzy Relational Database models (Chapter II), which are based on the relational model, extend this so that vague and uncertain information can be stored and/or treated with or without fuzzy logic (see Chapter I). The FuzzyEER Model (see Chapter IV) is an extension of the EER Model for creating conceptual schemas with fuzzy semantics and notations. This extension is a good eclectic synthesis between different models (see Chapter III) and provides new and useful definitions: fuzzy attributes, fuzzy entities, fuzzy relationships, fuzzy specializations, and so forth.

scholarly journals Functional Dependencies Analyse in Fuzzy Relational Database Models

2011 ◽  
Vol 2 (2) ◽  
Author(s):  
Miljan Vučetić
Keyword(s):  
Fuzzy Logic ◽  
Set Theory ◽  
Fuzzy Set ◽  
Relational Database ◽  
Fuzzy Set Theory ◽  
Uncertain Information ◽  
Functional Dependencies ◽  
Literature Overview ◽  
Database Models

This paper presents a literature overview of Fuzzy Relational Database Models with emphasis on the role of functional dependencies in logical designing and modeling. The aim is the analysis of recent results in this field. Fuzzy set theory is widely applied for the classical relational database extensions resulting in numerous contributions. This is because fuzzy sets and fuzzy logic are powerful tool for manilupating imprecise and uncertain information. A significant body of research in efficient designing FRDM has been developed over the last decades. Knowing the set of functional dependencies, database managers have a chance to normalize the same eliminating redundancy and data anomalies. In this paper we have considered the most important results in this field.

A Literature Overview of Fuzzy Database Modeling

2008 ◽  
pp. 187-207 ◽  
Author(s):  
Z.. M. Ma
Keyword(s):  
Relational Databases ◽  
Object Oriented ◽  
Data Models ◽  
Relational Model ◽  
Complex Objects ◽  
Database Modeling ◽  
Database Models ◽  
Fuzzy Database ◽  
Conceptual Data ◽  
Object Oriented Databases

Fuzzy set theory has been extensively applied to extend various data models and resulted in numerous contributions, mainly with respect to the popular relational model or to some related form of it. To satisfy the need of modeling complex objects with imprecision and uncertainty, recently many researches have been concentrated on fuzzy semantic (conceptual) and object-oriented data models. This chapter reviews fuzzy database modeling technologies, including fuzzy conceptual data models and database models. Concerning fuzzy database models, fuzzy relational databases, fuzzy nested relational databases, and fuzzy object-oriented databases are discussed, respectively.

New Trends in Databases to NonSQL Databases

2021 ◽  
pp. 791-799
Author(s):  
Antonio Sarasa-Cabezuelo
Keyword(s):  
Big Data ◽  
Information Processing ◽  
Real Time ◽  
Relational Databases ◽  
Data Models ◽  
Relational Model ◽  
Alternative Mechanism ◽  
New Models ◽  
Database Models

The appearance of the “big data” phenomenon has meant a change in the storage and information processing needs. This new context is characterized by 1) enormous amounts of information are available in heterogeneous formats and types, 2) information must be processed almost in real time, and 3) data models evolve periodically. Relational databases have limitations to respond to these needs in an optimal way. For these reasons, some companies such as Google or Amazon decided to create new database models (different from the relational model) that solve the needs raised in the context of big data without the limitations of relational databases. These new models are the origin of the so-called NonSQL databases. Currently, NonSQL databases have been constituted as an alternative mechanism to the relational model and its use is widely extended. The main objective of this chapter is to introduce the NonSQL databases.

A Literature Overview of Fuzzy Database Modeling

2009 ◽  
pp. 105-125 ◽  
Author(s):  
Z.M. Ma
Keyword(s):  
Relational Databases ◽  
Object Oriented ◽  
Data Models ◽  
Relational Model ◽  
Complex Objects ◽  
Database Modeling ◽  
Database Models ◽  
Fuzzy Database ◽  
Conceptual Data ◽  
Object Oriented Databases

Fuzzy set theory has been extensively applied to extend various data models and resulted in numerous contributions, mainly with respect to the popular relational model or to some related form of it. To satisfy the need of modeling complex objects with imprecision and uncertainty, recently many researches have been concentrated on fuzzy semantic (conceptual) and object-oriented data models. This chapter reviews fuzzy database modeling technologies, including fuzzy conceptual data models and database models. Concerning fuzzy database models, fuzzy relational databases, fuzzy nested relational databases, and fuzzy object-oriented databases are discussed, respectively.

A Literature Overview of Fuzzy Database Modeling

2011 ◽  
pp. 167-196
Author(s):  
Z. M. Ma
Keyword(s):  
Relational Databases ◽  
Object Oriented ◽  
Data Models ◽  
Relational Model ◽  
Complex Objects ◽  
Database Modeling ◽  
Database Models ◽  
Fuzzy Database ◽  
Conceptual Data ◽  
Object Oriented Databases

Fuzzy set theory has been extensively applied to extend various data models and resulted in numerous contributions, mainly with respect to the popular relational model or to some related form of it. To satisfy the need of modeling complex objects with imprecision and uncertainty, recently many researches have been concentrated on fuzzy semantic (conceptual) and object-oriented data models. This chapter reviews fuzzy database modeling technologies, including fuzzy conceptual data models and database models. Concerning fuzzy database models, fuzzy relational databases, fuzzy nested relational databases, and fuzzy object-oriented databases are discussed, respectively.

scholarly journals The Development and Usage of a Relational Database Design Tool for Educational Purposes

10.28945/3199 ◽  
2008 ◽  
Author(s):  
Milos Bogdanovic ◽  
Aleksandar Stanimirovic ◽  
Nikola Davidovic ◽  
Leonid Stoimenov
Keyword(s):  
Relational Database ◽  
Design Patterns ◽  
Relational Databases ◽  
Conceptual Modeling ◽  
Database Design ◽  
Design Tool ◽  
Relational Model ◽  
Modular Architecture ◽  
Data Definition ◽  
Entity Relationship

Most universities where students study informational technologies and computer science have an introductory course dealing with the development and design of databases. These courses often include usage of database design tools. In this paper, the #EER tool is presented, the task of which is to make the process of relational databases design easier for the students and partially automatize it. The tool evolved due to the experience in using similar tools for educational purposes. It enables fast and efficient development of the relational database conceptual model and its automatized compilation into a relational model and further to data definition language (DDL) commands. #EER tool is based on the extended entity-relationship (EER) model for conceptual modeling of relational databases. Modular architecture of the tool, the development of which is based on the usage of the design patterns, along with the benefits that its usage brings, is also presented.

Converting a Legacy Database to Object-Oriented Database

2005 ◽  
pp. 99-104
Author(s):  
Reda Alhajj ◽  
Faruk Polat
Keyword(s):  
Relational Database ◽  
Relational Databases ◽  
Object Oriented ◽  
Professional Staff ◽  
Relational Model ◽  
Object Oriented Technology ◽  
The People ◽  
Two Generations ◽  
Object Oriented Databases ◽  
Object Oriented Database

We present an approach to transfer content of an existing conventional relational database to a corresponding existing object-oriented database. The major motivation is having organizations with two generations of information systems; the first is based on the relational model, and the second is based on the object-oriented model. This has several drawbacks. First, it is impossible to get unified global reports that involve information from the two databases without providing a wrapper that facilitates accessing one of the databases within the realm of the other. Second, organizations should keep professional staff familiar with the system. Finally, most of the people familiar with the conventional relational technology are willing to learn and move to the emerging object-oriented technology. Therefore, one appropriate solution is to transfer content of conventional relational databases into object-oriented databases; the latter are extensible by nature, hence, are more flexible to maintain. However, it is very difficult to extend and maintain a conventional relational database.

scholarly journals Towards the methodology for development of fuzzy relational database applications

2011 ◽  
Vol 8 (1) ◽  
pp. 27-40 ◽  
Author(s):  
Srdjan Skrbic ◽  
Milos Rackovic ◽  
Aleksandar Takaci
Keyword(s):  
Fuzzy Logic ◽  
Relational Database ◽  
Data Model ◽  
Relational Databases ◽  
Model Development ◽  
Relational Data ◽  
Database Applications ◽  
Case Tool ◽  
Relational Data Model ◽  
Fuzzy Database

In this paper we examine the possibilities to extend the relational data model with the mechanisms that can handle imprecise, uncertain and inconsistent attribute values using fuzzy logic and fuzzy sets. We present a fuzzy relational data model which we use for fuzzy knowledge representation in relational databases that guarantees the model in 3rd normal form. We also describe the CASE tool for the fuzzy database model development which is apparently the first implementation of such a CASE tool. In this sense, this paper presents a leap forward towards the specification of a methodology for fuzzy relational database applications development.

scholarly journals A Hybrid Relational Database Model for Uncertain and Imprecise Information

2020 ◽  
Vol 8 (3) ◽  
Author(s):  
Hoa Nguyen
Keyword(s):  
Fuzzy Set ◽  
Relational Database ◽  
Uncertain Information ◽  
Database Model ◽  
Redundant Data ◽  
Probabilistic Database ◽  
Imprecise Information ◽  
Real World Applications ◽  
Database Models ◽  
Algebraic Operations

Recent years, many fuzzy or probabilistic database models have been built for representing and handling imprecise or uncertain information of objects in real-world applications. However, relational database models combining the relevance and strength of both fuzzy set and probability theories have rarely been proposed. This paper introduces a new relational database model, as a hybrid one combining consistently fuzzy set theory and probability theory for modeling and manipulating uncertain and imprecise information, where the uncertainty and imprecision of a relational attribute value are represented by a fuzzy probabilistic triple, the computation and combination of relational attribute values are implemented by using the probabilistic interpretation of binary relations on fuzzy sets, and the elimination of redundant data is dealt with by coalescing e-equivalent tuples. The basic concepts of the classical relational database model are extended in this new model. Then the relational algebraic operations are formally defined accordingly. A set of the properties of the relational algebraic operations is also formulated and proven.

Fuzzy Database Modeling

2005 ◽  
pp. 250-257 ◽  
Author(s):  
Z. M. Ma
Keyword(s):  
Fuzzy Logic ◽  
Real World ◽  
Data Models ◽  
Relational Model ◽  
Uncertain Information ◽  
Database Modeling ◽  
Related Form ◽  
Database Research ◽  
Classical Models ◽  
Fuzzy Database

A major goal for database research has been the incorporation of additional semantics into the data model. Classical data models often suffer from their incapability of representing and manipulating imprecise and uncertain information that may occur in many real-world applications. Since the early 1980s, Zadeh’s fuzzy logic (Zadeh, 1965) has been used to extend various data models. The purpose of introducing fuzzy logic in database modeling was to enhance the classical models such that uncertain and imprecise information can be represented and manipulated. This resulted in numerous contributions, mainly with respect to the popular relational model or to some related form of it.

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