Fuzzy And Uncertain Object Oriented Databases

Enriching database models so as to allow the user to deal with fuzzy and uncertain information has been of scientists' concern for years. This resulted in numerous contributions, mainly with respect to the popular relational model or to some related form of it. The experience was instructive, although still far from concrete applications. The time has come that the advantages of object-oriented databases are acknowledged outside the research and academic worlds and a breakthrough of new commercial softwares is observed. Lately research has been devoted to the endowment of this type of databases with more real-world reflecting semantics. It proved that the object-oriented paradigm lends itself extremely well to it. This is very promising and opens new perspectives for the availability of new-generation database products in the near future. The book presents the latest research results in dealing with fuzziness and uncertainty in object-oriented databases. Contents:Foreword (R Yager)Preface (R de Caluwe)Basic Notions and Rationale of the Integration of Uncertainty Management and Object-Oriented Databases (R de Caluwe et al.)A Hierarchical Model of Fuzzy Classes (J-P Rossazza et al.)Modelling Impreciseness and Uncertainty in the Object-Oriented Data Model — A Similarity-Based Approach (R George et al.)Extending a Graph-Based Data Model to Manage Fuzzy and Uncertain Information (G Bordogna et al.)The UFO Database Model: Dealing with Imperfect Information (N van Gyseghem & R de Caluwe)Fuzzy Object-Oriented Data Model and Fuzzy Association Algebra (S Na & S Park) Readership: Researchers and engineers interested in databases and software engineering/programming. keywords:Concepts of Fuzzy Databases;Modeling of Fuzzy Data;Modeling of Uncertain Data;Modeling of Databases;Modeling of Object-Oriented Databases;Modeling of Fuzziness in Databases;Modeling of Uncertainty in Databases;Fuzzy Databases;Fuzzy Object-Oriented Databases;Uncertain Object-Oriented Databases

Enriching database models to allow the user to deal with fuzzy and uncertain information has been of scientists' concern for years. This book presents the latest research results in dealing with fuzziness and uncertainty in object-oriented databases. The readership will be researchers and engineers interested in databases and software engineering programming.

Readers will get a complete understanding of the notions, techniques, and methods related to the research and developments of fuzzy object-oriented databases from the book, which will serve as a starting point and a reference for their research and developments."--BOOK JACKET.

"This reference expands the field of database technologies through four-volumes of in-depth, advanced research articles from nearly 300 of the world's leading professionals"--Provided by publisher.

"This book provides comprehensive coverage and definitions of the most important issues, concepts, trends, and technologies in fuzzy topics applied to databases, discussing current investigation into uncertainty and imprecision management by means of fuzzy sets and fuzzy logic in the field of databases and data mining. It offers a guide to fuzzy information processing in databases"--Provided by publisher.

"This set of books represents a detailed compendium of authoritative, research-based entries that define the contemporary state of knowledge on technology"--Provided by publisher.

It is not an exaggeration to view Professor Lee's book," Software Engineer ing with Computational Intelligence," or SECI for short, as a pioneering contribution to software engineering. Breaking with the tradition of treat ing uncertainty, imprecision, fuzziness and vagueness as issues of peripheral importance, SECI moves them much closer to the center of the stage. It is ob vious, though still not widely accepted, that this is where these issues should be, since the real world is much too complex and much too ill-defined to lend itself to categorical analysis in the Cartesian spirit. As its title suggests, SECI employs the machineries of computational intel ligence (CI) and, more or less equivalently, soft computing (SC), to deal with the foundations and principal issues in software engineering. Basically, CI and SC are consortia of methodologies which collectively provide a body of con cepts and techniques for conception, design, construction and utilization of intelligent systems. The principal constituents of CI and SC are fuzzy logic, neurocomputing, evolutionary computing, probabilistic computing, chaotic computing and machine learning. The leitmotif of CI and SC is that, in general, better performance can be achieved by employing the constituent methodologies of CI and SC in combination rat her than in a stand-alone mode. In what follows, I will take the liberty of focusing my attention on fuzzy logic and fuzzy set theory, and on their roles in software engineering. But first, a couple of points of semantics which are in need of clarification.

This book covers a fast-growing topic in great depth and focuses on the technologies and applications of probabilistic data management. It aims to provide a single account of current studies in probabilistic data management. The objective of the book is to provide the state of the art information to researchers, practitioners, and graduate students of information technology of intelligent information processing, and at the same time serving the information technology professional faced with non-traditional applications that make the application of conventional approaches difficult or impossible.