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.

A Type-2 Fuzzy Relational Database Model

2017 ◽  
Author(s):  
Nguyen Hoa
Keyword(s):  
Relational Database ◽  
Fuzzy Numbers ◽  
Extension Principle ◽  
Membership Degree ◽  
Database Model ◽  
Real World Applications ◽  
Database Models ◽  
Algebraic Operations

This paper introduces a type-2 fuzzy relational database model (T-2FRDB) as an extension of type-1 fuzzy relational database models with a full set of basic fuzzy relational algebraic operations that can represent and query uncertain and imprecise information in real world applications. In this model, the membership degree of tuples in a fuzzy relation is represented by fuzzy numbers on [0,1], and fuzzy relational algebraic operations are defined by using the extension principle for computing minimum and maximum values of such fuzzy numbers. Some properties of the type-2 fuzzy relational algebraic operations in T-2FRDB are also formulated and proven as extensions of their counterpart in the type-1 fuzzy relational database models. DOI: 10.32913/rd-ict.vol3.no14.352

scholarly journals A probabilistic relational database model and algebra

2015 ◽  
Vol 31 (4) ◽  
pp. 305
Author(s):  
Hoa Nguyen
Keyword(s):  
Relational Database ◽  
Functional Dependency ◽  
Uncertain Information ◽  
Database Model ◽  
Algebraic Operations ◽  
And Algebra ◽  
Attribute Value

This paper introduces a probabilistic relational database model, called PRDB, for representing and querying uncertain information of objects in practice. To develop the PRDB model, first, we represent the relational attribute value as a pair of probabilistic distributions on a set for modeling the possibility that the attribute can take one of the values of the set with a probability belonging to the interval which is inferred from the pair of probabilistic distributions. Next, on the basis representing such attribute values, we formally define the notions as the schema, relation, probabilistic functional dependency and probabilistic relational algebraic operations for PRDB. In addition, a set of the properties of the probabilistic relational algebraic operations in PRDB also are formulated and proven.

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.

scholarly journals EXTENDING RELATIONAL DATABASE MODEL FOR UNCERTAIN INFORMATION

2019 ◽  
Vol 35 (4) ◽  
pp. 355-372
Author(s):  
Hòa Nguyễn
Keyword(s):  
Relational Database ◽  
Probability Measures ◽  
Uncertain Information ◽  
Probabilistic Interpretation ◽  
Binary Relations ◽  
Finite Sets ◽  
New Model ◽  
Database Model ◽  
Combination Strategies ◽  
Algebraic Operations

In this paper, we propose a new probabilistic relational database model, denote by PRDB, as an extension of the classical relational database model where the uncertainty of relational attribute values and tuples are respectively represented by finite sets and probability intervals. A probabilistic interpretation of binary relations on finite sets is proposed for the computation of their probability measures. The combination strategies on probability intervals are employed to combine attribute values and compute uncertain membership degrees of tuples in a relation. The fundamental concepts of the classical relational database model are extended and generalized for PRDB. Then, the probabilistic relational algebraic operations are formally defined accordingly in PRDB. In addition, a set of the properties of the algebraic operations in this new model also are formulated and proven.

scholarly journals A New Approach of Functional Dependency in a Neutrosophic Relational Database Model

2019 ◽  
Vol 8 (2) ◽  
pp. 44-48
Author(s):  
Soumitra De ◽  
Jaydev Mishra
Keyword(s):  
Relational Database ◽  
Classical Case ◽  
Functional Dependency ◽  
Neutrosophic Set ◽  
Uncertain Information ◽  
Neutrosophic Sets ◽  
New Approach ◽  
Vague Set ◽  
Database Model ◽  
Relational Data Model

In order to model the imprecise and uncertain information, different classical relational data model have been studied in literature using vague set theory. However, neutrosophic set, as a generalized vague set, has more powerful ability to process fuzzy information than vague set. In this paper, we have proposed a neutrosophic relational database model and have defined a new kind of neutrosophic functional dependency (called  -nfd) based on the -equality of tuples and the similarity measure of neutrosophic sets. Next, we present a set of sound neutrosophic inference rules which are similar to Armstrong’s axioms for the classical case. Finally, partial  -nfdand neutrosophic key have been studied with the new notion of  -nfdand also tested.

scholarly journals A Comparative Study of NoSQL and Relational Database

2017 ◽  
Vol 1 (1) ◽  
pp. 1-4 ◽  
Author(s):  
Douglas Kunda ◽  
Hazael Phiri
Keyword(s):  
Big Data ◽  
Web 2.0 ◽  
Relational Database ◽  
Relational Databases ◽  
Query Language ◽  
The Other ◽  
Database Model ◽  
Nosql Database ◽  
Database Models ◽  
Year 2000

Relational Database and NoSQL are competing types of database models. The former has been in existence since 1979 and the latter since the year 2000. The demands of modern applications especially in web 2.0, 3.0 and big data have made NoSQL a popular database of choice. Choosing an appropriate database model to use is an important decision that developers must make based on the features of a given database model. This paper compares the features of Relational Databases and NoSQL to establish which database is better at supporting demands of modern applications. The paper also brings out the challenges of NoSQL. Finally, the paper concludes by determining whether Relational Databases would completely be replaced by NoSQL database models. The findings revealed that, Relational Databases are based on ACID model which emphasizes better consistency, security and offers a standard query language. However, Relational Databases have poor scalability, weak performance, cost more, face availability challenges when supporting large number of users and handle limited volume of data. NoSQL, on the other hand is based on the BASE model, which emphasizes greater scalability and provides a flexible schema, offers better performance, mostly open source, cheap but, lacks a standard query language and does not provide adequate security mechanisms. Both databases will continue to exist alongside each other with none being better than the other. The choice of the database to use will depend on the nature of the application being developed. Each database type has its own challenges and strengths, with relational database lacking of support for unstructured data while NoSQL lacks standardization and has poor security. Modern applications in web 2.0, 3.0 and big data are well suited to use NoSQL but, there are still many applications that rely on Relational Databases.

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 FUZZY RELATIONAL DATABASE MODEL AND MANAGEMANT SYSTEM FOR IMPRECISE INFORMATION

2021 ◽  
Vol 37 (2) ◽  
pp. 145-162
Author(s):  
Hoa Nguyen ◽  
Nguyen Thi Uyen Nhi ◽  
Le Nhat Duy
Keyword(s):  
Open Source ◽  
Relational Database ◽  
Management System ◽  
Fuzzy Membership ◽  
Membership Degree ◽  
Database Model ◽  
Imprecise Information ◽  
Source Management

This paper introduces a fuzzy relational database model (FRDB) and the management system for it. FRDB is built by extending the classical relational database model with the fuzzy membership degree of tuples in relations. The management system for FRDB with the querying language like SQL is built by using a classical open-source management system.

Incomplete information in a relational database

1980 ◽  
Vol 3 (3) ◽  
pp. 363-377
Author(s):  
John Grant
Keyword(s):  
Incomplete Information ◽  
Relational Database ◽  
Functional Dependency ◽  
Relational Algebra ◽  
Database Model ◽  
Character String

In this paper we investigate the inclusion of incomplete information in the relational database model. This is done by allowing nonatomic entries, i.e. sets, as elements in the database. A nonatomic entry is interpreted as a set of possible elements, one of which is the correct one. We deal primarily with numerical entries where an allowed set is an interval, and character string entries. We discuss the various operations of the relational algebra as well as the notion of functional dependency for the database model.

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