An Overview of Fuzzy Approaches to Flexible Database Querying

2009 ◽  
pp. 135-156 ◽  
Author(s):  
Slawomir Zadrozny ◽  
Guy de Tré ◽  
Rita de Caluwe ◽  
Janusz Kacprzyk
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Object Oriented ◽  
Database Systems ◽  
Database Modeling ◽  
Database Querying ◽  
Object Oriented Database ◽  
Flexible Querying ◽  
Natural Way

In reality, a lot of information is available only in an imperfect form. This might be due to imprecision, vagueness, uncertainty, incompleteness, or ambiguities. Traditional database systems can only adequately cope with perfect data. Among others, fuzzy set theory has been applied to deal with imperfections of data in a more natural way and to enhance the accessibility of databases. In this chapter, we give an overview of main trends in the research on flexible querying techniques that are based on fuzzy set theory. Both querying techniques for traditional databases as well as querying techniques for fuzzy databases are described. The discussion comprises both the relational and the object-oriented database modeling approaches.

An Overview of Fuzzy Approaches to Flexible Database Querying

2011 ◽  
pp. 34-54 ◽  
Author(s):  
Slawomir Zadrozny ◽  
Guy de Tré ◽  
Rita de Caluwe ◽  
Janusz Kacprzyk
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Object Oriented ◽  
Database Systems ◽  
Database Modeling ◽  
Database Querying ◽  
Object Oriented Database ◽  
Flexible Querying ◽  
Natural Way

In reality, a lot of information is available only in an imperfect form. This might be due to imprecision, vagueness, uncertainty, incompleteness, or ambiguities. Traditional database systems can only adequately cope with perfect data. Among others, fuzzy set theory has been applied to deal with imperfections of data in a more natural way and to enhance the accessibility of databases. In this chapter, we give an overview of main trends in the research on flexible querying techniques that are based on fuzzy set theory. Both querying techniques for traditional databases as well as querying techniques for fuzzy databases are described. The discussion comprises both the relational and the object-oriented database modeling approaches.

Fuzzy XQuery

2015 ◽  
pp. 158-198
Author(s):  
José Ángel Labbad ◽  
Ricardo R. Monascal ◽  
Leonid Tineo
Keyword(s):  
Performance Analysis ◽  
Open Source ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Database Systems ◽  
Query Languages ◽  
Xml Data ◽  
Fuzzy Query ◽  
Query Engine

Traditional database systems and languages are very rigid. XML data and query languages are not the exception. Fuzzy set theory is an appropriate tool for solving this problem. In this sense, Fuzzy XQuery was proposed as an extension of the XQUERY standard. This language defines the xs:truth datatype, the xml:truth attribute and allows the definition and use of fuzzy terms in queries. The main goal of this chapter is to show a high coupling implementation of Fuzzy XQuery within eXist-db, an open source XML DBMS. This extension strategy could also be used with other similar tools. This chapter also presents a statistical performance analysis of the extended fuzzy query engine using the XMark benchmark with user defined fuzzy terms. The study presents promising results.

Evaluation of Quantified Statements Using Gradual Numbers

2011 ◽  
pp. 246-269 ◽  
Author(s):  
Ludovic Liétard ◽  
Daniel Rocacher
Keyword(s):  
Decision Making ◽  
Expert Systems ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Relational Databases ◽  
Fuzzy Numbers ◽  
Theoretical Background ◽  
Definition Of ◽  
Flexible Querying

This chapter is devoted to the evaluation of quantified statements which can be found in many applications as decision making, expert systems, or flexible querying of relational databases using fuzzy set theory. Its contribution is to introduce the main techniques to evaluate such statements and to propose a new theoretical background for the evaluation of quantified statements of type “Q X are A” and “Q B X are A.” In this context, quantified statements are interpreted using an arithmetic on gradual numbers from Nf, Zf, and Qf. It is shown that the context of fuzzy numbers provides a framework to unify previous approaches and can be the base for the definition of new approaches.

Rough Sets

2011 ◽  
pp. 129-151
Author(s):  
Theresa Beaubouef ◽  
Frederick E Petry
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Fuzzy Set ◽  
Rough Sets ◽  
Rough Set Theory ◽  
Object Oriented ◽  
Uncertainty Management ◽  
Database Model ◽  
Management Of Uncertainty ◽  
Object Oriented Database

This chapter discusses ways in which rough set theory can enhance databases by allowing for the management of uncertainty. Rough sets can be integrated into an underlying database model, relational or object oriented, and also used in design and querying of databases. Because rough sets are a versatile theory, they can also be combined with other theories. The authors discuss the rough relational database model, the rough object oriented database model, and fuzzy set and intuitionistic set extensions to each of these models. Comparisons and benefits of the various approaches are discussed, illustrating the usefulness and versatility of rough sets for uncertainty management in databases.

UNCERTAIN AND FUZZY OBJECT BASES: A DATA MODEL AND ALGEBRAIC OPERATIONS

2011 ◽  
Vol 19 (02) ◽  
pp. 275-305 ◽  
Author(s):  
TRU H. CAO ◽  
HOA NGUYEN
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Object Oriented ◽  
Possibility Theory ◽  
Object Properties ◽  
Common Framework ◽  
Formal Basis ◽  
Object Oriented Systems ◽  
Is Value

Fuzzy set theory and probability theory are complementary for soft computing, in particular object-oriented systems with imprecise and uncertain object properties. However, current fuzzy object-oriented data models are mainly based on fuzzy set theory or possibility theory, and lack of a rigorous algebra for querying and managing uncertain and fuzzy object bases. In this paper, we develop an object base model that incorporates both fuzzy set values and probability degrees to handle imprecision and uncertainty. A probabilistic interpretation of relations on fuzzy sets is introduced as a formal basis to coherently unify the two types of measures into a common framework. The model accommodates both class attributes, representing declarative object properties, and class methods, representing procedural object properties. Two levels of property uncertainty are taken into account, one of which is value uncertainty of a definite property and the other is applicability uncertainty of the property itself. The syntax and semantics of the selection and other main data operations on the proposed object base model are formally defined as a full-fledged algebra.

AGGREGATES COMPUTED OVER FUZZY SETS AND THEIR INTEGRATION INTO SQLf

2008 ◽  
Vol 16 (06) ◽  
pp. 761-792 ◽  
Author(s):  
PATRICK BOSC ◽  
LUDOVIC LIETARD
Keyword(s):  
Fuzzy Sets ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Relational Databases ◽  
Query Language ◽  
Fuzzy Integral ◽  
Flexible Querying

The SQLf query language is an extension of SQL to flexible querying of regular relational databases using fuzzy set theory. In this context, atomic predicates (called vague or fuzzy predicates) are expressing preferences and are defined by fuzzy sets. The main purpose of flexible querying is to provide the user with a set of discriminated answers (in the form of a fuzzy set). Until now, the use of aggregates (such as maximum or average) in SQLf queries is limited to the particular case where the aggregate applies to a crisp set. The objective of this paper is to propose an approach to define SQLf queries where the aggregate applies to a fuzzy set of items. The approach proposed here can indeed be seen as a generalization of Sugeno's fuzzy integral.

scholarly journals Hierarchical Fuzzy Sets to Query Possibilistic Databases

2011 ◽  
pp. 299-324
Author(s):  
Rallou Thomopoulos ◽  
Patrice Buche ◽  
Ollivier Haemmerlé
Keyword(s):  
Fuzzy Sets ◽  
Set Theory ◽  
Current Literature ◽  
Fuzzy Set ◽  
User Interfaces ◽  
Fuzzy Set Theory ◽  
Relational Databases ◽  
Experimental Results ◽  
Relational Model ◽  
Flexible Querying

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: first, flexible querying of imprecise data in the relational model and, second, the introduction of fuzziness in hierarchies. Concerning the latter point, we develop an aspect where there is a lack of study in current literature: fuzzy sets whose definition domains are hierarchies. Hence, we propose the concept of hierarchical fuzzy set and present its properties. We present its application in the MIEL flexible querying system for the querying of two imprecise relational databases, including user interfaces and experimental results.

Flexible Querying Techniques Based on CBR

2011 ◽  
pp. 167-190
Author(s):  
Guy De Tré ◽  
Marysa Demoor ◽  
Bert Callens ◽  
Lise Gosseye
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Possibility Theory ◽  
Case Based Reasoning ◽  
Similarity Matching ◽  
Untreated Case ◽  
Flexible Querying ◽  
Case Based

In case-based reasoning (CBR), a new untreated case is compared to cases that have been treated earlier, after which data from the similar cases (if found) are used to predict the corresponding unknown data values for the new case. Because case comparisons will seldom result in an exact-similarity matching of cases and the conventional CBR approaches do not efficiently deal with such imperfections, more advanced approaches that adequately cope with these imperfections can help to enhance CBR. Moreover, CBR in its turn can be used to enhance flexible querying. In this chapter, we describe how fuzzy set theory can be used to model a gradation in similarity of the cases and how the inevitable uncertainty that occurs when predictions are made can be handled using possibility theory resulting in what we call flexible CBR. Furthermore, we present how and under which conditions flexible CBR can be used to enhance flexible querying of regular databases.

Sign in / Sign up

Export Citation Format

Share Document