Knowledge Management in Fuzzy Databases
Author:   Olga Pons ,  Maria A. Vila ,  Janusz Kacprzyk
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   2000 ed.
Volume:   39
ISBN:  

9783790812558


Pages:   386
Publication Date:   17 November 1999
Format:   Hardback
Availability:   In Print   Availability explained
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Knowledge Management in Fuzzy Databases


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Overview

"The volume presents recent developments in the introduction of fuzzy, probabilistic and rough elements into basic components of fuzzy databases, and their use (notably querying and information retrieval), from the point of view of data mining and knowledge discovery. The main novel aspect of the volume is that issues related to the use of fuzzy elements in databases, database querying, information retrieval, etc. are presented and discussed from the point of view, and for the purpose of data mining and knowledge discovery that are ""hot topics"" in recent years. This may be useful for both people involved in theoretical research, education, and even the design and implementation of working computer systems."

Full Product Details

Author:   Olga Pons ,  Maria A. Vila ,  Janusz Kacprzyk
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Physica-Verlag GmbH & Co
Edition:   2000 ed.
Volume:   39
Dimensions:   Width: 15.50cm , Height: 2.30cm , Length: 23.50cm
Weight:   1.640kg
ISBN:  

9783790812558


ISBN 10:   3790812552
Pages:   386
Publication Date:   17 November 1999
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Fuzziness in Databases: Basic Aspects.- Fuzziness in Databases: Operational Aspects.- Data Mining and Knowledge Discovery Via Querying, Retrieval and Summarization.- Using Rough Sets and Evidence Theory for Handling Uncertainty in Data Mining.

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