Object-Oriented Features in Oracle

2011 ◽  
pp. 31-50
Author(s):  
Johanna Wenny Rahayu ◽  
David Tanier ◽  
Eric Pardede

In this chapter, we will describe Oracle™ features that can be used to support the implementation of an object-oriented model. As an overview, Section 2.1 will outline some of the original features within a standard relational model. The next sections will illustrate the additional object-oriented features. We will use these new features for our implementation in the subsequent chapters.

2008 ◽  
pp. 187-207 ◽  
Author(s):  
Z.. M. Ma

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.


2009 ◽  
pp. 105-125 ◽  
Author(s):  
Z.M. Ma

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.


2011 ◽  
pp. 167-196
Author(s):  
Z. M. Ma

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.


Author(s):  
TIMO NIEMI ◽  
MARKO JUNKKARI ◽  
KALERVO JÄRVELIN

Next generation information systems (NGISs) have to support the manipulation of data-oriented, behavioral and deductive aspects of application domains. Many modeling methods, e.g. UML and other object-oriented modeling methods offer primitives for modeling data-oriented and behavioral aspects but they do not support the modeling of deductive aspects. In addition, NGISs may be implemented by several separate software/database systems that are based on different paradigms. Therefore it is not appropriate to use such a modeling method which is based on one paradigm. In NGISs it is essential to integrate the value-oriented approach with the object-oriented approach. We develop a relational deductive object-oriented modeling (RDOOM) approach for NGISs. Our goal is to combine into one modeling method, the navigation power of the relational model, the modeling power of the object-orientation and the inference power of the deductive (logical) framework. It is obvious that in NGISs complex and large specifications have to be embedded in application-specific concepts and structures that are defined beforehand for users to facilitate their query formulation. The detection and specification of application-specific concepts and structures means a new challenge for analysis methods. We show that on the basis of the primitives of RDOOM it is possible to represent this kind of application-specific information in a natural way. It is also necessary that the appropriateness and adequacy of application-specific concepts and structures can be tested before their expensive design and implementation phases. For the definition of these concepts and structures a diagrammatic representation typical of many modeling methods is not sufficient. Rather, a precise and executable representation is needed. Especially the complex and large derivation rules behind deductive concepts cannot be expressed precisely with diagrammatic representations. We develop set-theoretical representations for our primitives. The precise representation of the result of systems analysis also gives a more substantial starting point for the design and implementation of NGISs.


Author(s):  
Hiroshi Sakai ◽  
◽  
Masahiro Inuiguchi ◽  

Rough sets and granular computing, known as new methodologies for computing technology, are now attracting great interest of researchers. This special issue presents 12 articles, and most of them were presented at the second Japanese workshop on Rough Sets held at Kyushu Institute of Technology in Tobata, Kitakyushu, Japan, on August 17-18, 2005. The first article studies the relation between rough set theory and formal concept analysis. These two frameworks are analyzed and connected by using the method of morphism. The second article introduces object-oriented paradigm into rough set theory, and object-oriented rough set models are proposed. Theoretical aspects of these new models are also examined. The third article considers relations between generalized rough sets, topologies and modal logics, and some topological properties of rough sets induced by equivalence relations are presented. The fourth article focuses on a family of polymodal systems, and theoretical aspects of these systems, like the completeness, are investigated. By means of combining polymodal logic concept and rough set theory, a new framework named multi-rough sets is established. The fifth article focuses on the information incompleteness in fuzzy relational models, and a generalized possibility-based fuzzy relational model is proposed. The sixth article presents a developed software EVALPSN (Extended Vector Annotated Logic Program with Strong Negation) and the application of this software to pipeline valve control. The seventh article presents the properties of attribute reduction in variable precision rough set models. Ten kinds of meaningful reducts are newly proposed, and hierarchical relations in these reducts are examined. The eighth article proposes attribute-value reduction for Kansei analysis using information granulation, and illustrative results for some databases in UCI Machine Learning Repository are presented. The ninth article investigates cluster analysis for data with errors tolerance. Two new clustering algorithms, which are based on the entropy regularized fuzzy c-means, are proposed. The tenth article applies binary decision trees to handwritten Japanese Kanji recognition. The consideration to the experimental results of real Kanji data is also presented. The eleventh article applies a rough sets based method to analysing the character of the screen-design in every web site. The obtained character gives us good knowledge to generate a new web site. The last article focuses on rule generation in non-deterministic information systems. For generating minimal certain rules, discernibility functions are introduced. A new algorithm is also proposed for handling every discernibility function. Finally, we would like to acknowledge all the authors for their efforts and contributions. We are very grateful to reviewers for their thorough and on-time reviews, too. We are also grateful to Prof. Toshio Fukuda and Prof. Kaoru Hirota, Editors-in-Chief of JACIII, for inviting us to serve as Guest Editors of this Journal, and to Mr. Uchino and Mr. Ohmori of Fuji Technology Press for their kind assistance in publication of this special issue.


Author(s):  
Esperenza Marcos ◽  
Paloma Caceres

In spite of the fact that relational databases still hold the first place in the market, object-oriented databases are becoming, each day, more widely accepted. Relational databases are suitable for traditional applications supporting management tasks such as payroll or library management. Recently, as a result of hardware improvements, more sophisticated applications have emerged. Engineering applications, such as CAD/CAM (Computer Aided Design/ Computer Aided Manufacturing), CASE (Computer Aided Software Engineering) or CIM (Computer Integrating Manufacturing), office automation systems, multimedia systems such as GIS (Geographic Information Systems) or medical information systems, can be characterized as consisting of complex objects related by complex interrelationships. Representing such objects and relationships in the relational model implies that the objects must be decomposed into a large number of tuples. Thus, a considerable number of joins is necessary to retrieve an object and, when tables are too deeply nested, performance is dramatically reduced (Bertino and Marcos, 2000).


Author(s):  
Reda Alhajj ◽  
Faruk Polat

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.


Author(s):  
Antonio Badia

The relational data model is the dominant paradigm in the commercial database market today, and it has been for several years. However, there have been challenges to the model over the years, and they have influenced its evolution and that of database technology. The object-oriented revolution that got started in programming languages arrived to the database area in the form of a brand new data model. The relational model managed not only to survive the newcomer but to continue becoming a dominant force, transformed into the object-relational model (also called extended relational, or universal) and relegating object-oriented databases to a niche product. Although this market has many nontechnical aspects, there are certainly important technical differences among the mentioned data models. In this article I describe the basic components of the relational, object-oriented, and object-relational data models. I do not, however, discuss query language, implementation, or system issues. A basic comparison is given and then future trends are discussed.


Sign in / Sign up

Export Citation Format

Share Document