Download Free Recent Issues On Fuzzy Databases Book in PDF and EPUB Free Download. You can read online Recent Issues On Fuzzy Databases and write the review.

First of all, I would like to congratulate Gabriella Pasi and Gloria Bordogna for the work they accomplished in preparing this new book in the series "Study in Fuzziness and Soft Computing". "Recent Issues on the Management of Fuzziness in Databases" is undoubtedly a token of their long-lasting and active involvement in the area of Fuzzy Information Retrieval and Fuzzy Database Systems. This book is really welcome in the area of fuzzy databases where they are not numerous although the first works at the crossroads of fuzzy sets and databases were initiated about twenty years ago by L. Zadeh. Only five books have been published since 1995, when the first volume dedicated to fuzzy databases published in the series "Study in Fuzziness and Soft Computing" edited by J. Kacprzyk and myself appeared. Going beyond books strictly speaking, let us also mention the existence of review papers that are part of a couple of handbooks related to fuzzy sets published since 1998. The area known as fuzzy databases covers a bunch of topics among which: -flexible queries addressed to regular databases, -the extension of the notion of a functional dependency, -data mining and fuzzy summarization, -querying databases containing imperfect attribute values represented thanks to possibility distributions.
This volume presents the results of approximately 15 years of work from researchers around the world on the use of fuzzy set theory to represent imprecision in databases. The maturity of the research in the discipline and the recent developments in commercial/industrial fuzzy databases provided an opportunity to produce this survey. In this introduction we will describe briefly how fuzzy databases fit into the overall design of database systems and then overview the organization of the text. FUZZY DATABASE LANDSCAPE The last five years have been witness to a revolution in the database research community. The dominant data models have changed and the consensus on what constitutes worthwhile research is in flux. Also, at this time, it is possible to gain a perspective on what has been accomplished in the area of fuzzy databases. Therefore, now is an opportune time to take stock of the past and establish a framework. A framework should assist in evaluating future research through a better understanding of the different aspects of imprecision that a database can model [ 1 l.
"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 book includes an introduction to fuzzy logic, fuzzy databases and an overview of the state of the art in fuzzy modeling in databases"--Provided by publisher.
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 book investigates the advent of soft computing and its applications in database technologies"--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 volume contains the proceedings of the Fifth International Conference on Database Systems for Advanced Applications (DASFAA '97). DASFAA '97 focused on advanced database technologies and their applications. The 55 papers in this volume cover a wide range of areas in the field of database systems and applications ? including the rapidly emerging areas of the Internet, multimedia, and document database systems ? and should be of great interest to all database system researchers and developers, and practitioners.
"This book confronts the problem of meaning by fusing together methods specific to different fields and exploring the computational efficiency and scalability of these methods"--Provided by publisher.
The digital revolution and the explosive growth of the internet have helped the collection of huge amounts of useful data of diverse characteristics, which is a valuable and intangible asset in any business of today. This book treats the new, emerging discipline of soft computing, which exploits this data through tolerance for imprecision and uncertainty to achieve solutions for complex problems. Soft computing methodologies include fuzzy sets, neural networks, genetic algorithms, Bayesian belief networks and rough sets, which are explored in detail through case studies and in-depth research. The advent of soft computing marks a significant paradigm shift in computing, with a wide range of applications and techniques which are presented and discussed in the chapters of this book.