Fuzzy Sets and Fuzzy Database Models

2013 ◽  
pp. 31-81
Author(s):  
Li Yan ◽  
Zongmin Ma ◽  
Fu Zhang
Keyword(s):  
Fuzzy Sets ◽  
Database Models ◽  
Fuzzy Database

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.

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.

ADAPTING QUERY REPRESENTATION TO IMPROVE RETRIEVAL IN A FUZZY DATABASE

1995 ◽  
Vol 03 (01) ◽  
pp. 57-77 ◽  
Author(s):  
JORGE GASOS ◽  
ANCA RALESCU
Keyword(s):  
Inverse Problem ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Data Model ◽  
Query Language ◽  
Database System ◽  
Retrieval Performance ◽  
User Facility ◽  
Fuzzy Database ◽  
Facial Images

We present an adjustment-to-user facility of a facial images database system in order to improve retrieval performance. The system uses linguistic (qualitative) descriptions, both in the data model and in the query language. These descriptions are internally represented as fuzzy sets. As the same linguistic descriptions can be used by different users to describe different values, the need of adjusting fuzzy sets, such that the user’s meaning is represented arises. We provide a method which, upon repeated queries by the same user, finds the best representation (as fuzzy set) of the linguistic descriptions given by the user in question. The method is based on an extension of the inverse problem of matching of fuzzy sets. Experiments show that when compared with the unadjusted system, significantly better results are obtained during the process of finding the best representation, and much better results after the best representation (given the whole database) is found.

Fuzzy Logic for Image Retrieval and Image Databases

2013 ◽  
pp. 221-238
Author(s):  
Li Yan ◽  
Z. M. Ma
Keyword(s):  
Fuzzy Logic ◽  
Image Retrieval ◽  
Fuzzy Sets ◽  
Large Scale ◽  
Image Data ◽  
Content Based Image Retrieval ◽  
Data Resource ◽  
Database Models ◽  
Image Query ◽  
Fuzzy Image

Fuzzy set theory has been extensively applied to the representation and processing of imprecise and uncertain data. Image data is becoming an important data resource with rapid growth in the number of large-scale image repositories. However, image data is fuzzy in nature, and imprecision and vagueness may exist in both image descriptions and query specifications. This chapter reviews some major work of image retrieval with fuzzy logic in the literature, including fuzzy content-based image retrieval and database support for fuzzy image retrieval. For the fuzzy content-based image retrieval, we present how fuzzy sets are applied for the extraction and representation of visual (colors, shapes, textures) features, similarity measures and indexing, relevance feedback, and retrieval systems. For the fuzzy image database retrieval, we present how fuzzy sets are applied for fuzzy image query processing based on a defined database models, and how various fuzzy database models can support image data management.

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