Knowledge Management in Fuzzy Databases

 Previously published in hardcover
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Previously published in hardcover
Olga Pons
608 g
235x155x21 mm

With contributions by some of the most outstanding researchers in the field
E. Trillas : Foreword.- Fuzziness in Databases: Basic Aspects : E.E. Kerre, G. Chen : Fuzzy Data Modeling at a Conceptual Level: Extending ER/EER Concepts.- A. Yazici, A. Cinar : Conceptual Modeling for the Design of Fuzzy Object Oriented Databases.- M. Nakata : On Inference Rules of Dependencies in Fuzzy Relational Data Models: Functional Dependencies.- R. De Calluwe, G. De Tré, B. Van der Cruyssen, F. Devos, P. Maesfranckx : Time Mangement in Fuzzy and Uncertain Object-Oriented Databases.- O. Maimon, A. Kandel, M. Last : Fuzzy Approach to Data Reliability.- Fuzziness in Databases: Operational Aspects : D. Dubois, M. Nakata, H. Prade : Extended Divisions for Flexible Queries in Relational Databases.- G. Chen : Fuzzy Functional Dependecy as a Sort of Semantic Knowledge: Representation, Preservation and Use.- A. Czinkóczky-Sali : A Combinatorial Characterization of Fuzzy Functional Dependencies.- M. Nakata : Formulation of Division Operators in Fuzzy Relational Databases.- Data Mining and Knowledge Discovery Via Querying, Retrieval and Summarization : Z.W. Ras : Intelligent Query Answering in DAKS.- P. Bosc, O. Pivert : SQLf Query Functionality on Top of a Regular Relational Database Management System.- J. Galindo, J.M. Medina, J.C. Cubero : How to Obtain the Fulfilment Degrees of a Query Using Fuzzy Relational Calculus.- J. Kacprzyk, S. Zadrozny : Data Mining via Fuzzy Querying over the Internet.- G. Bordogna, P. Bosc, G. Pasi : Extended Boolean Information Retrieval in Terms of Fuzzy Inclusion.- J. Chen, A. Mikulcic, D.H. Kraft : An Integrated Approach to Information Retrieval with Fuzzy Clustering and Fuzzy Inferencing.- R.R. Yager : Retrieval from Multimedia Databases Using Fuzzy Temporal Concepts.- M. Rifqi, S. Monties : Fuzzy Prototypes for Fuzzy Data Mining.- M. Bellmann, N. Vojdani : Creating Business Knowledge by Fuzzy Data Mining.- Using Rough Sets and Evidence Theory for Handling Uncertainty in Data Mining : S.S. Anand, J.G. Hughes, D.A. Bell : Towards the Handling of Uncertainty in Knowledge Discovery in Databeses.- M. Kryszkiewicz, H. Rybinski : Reducing Information Systems with Uncertain Real Value Attributes.- F. Machuca, M. Millán : Enhancing Query Processing in Extended Relational Database Systems via Rough Set Theory to Exploit Data Mining Potential.- M.C. Fernandez-Baizán, E. Menasalvas Ruiz, J.M. Peña Sánchez : Integrating RDMS and Data Mining Capabilities Using Rough Sets.
1. When I was asked by the editors of this book to write a foreword, I was seized by panic. Obviously, neither I am an expert in Knowledge Representation in Fuzzy Databases nor I could have been beforehand unaware that the book's contributors would be some of the most outstanding researchers in the field. However, Amparo Vila's gentle insistence gradually broke down my initial resistance, and panic then gave way to worry. Which paving stones did I have at my disposal for making an entrance to the book? After thinking about it for some time, I concluded that it would be pretentious on my part to focus on the subjects which are dealt with directly in the contributions presented, and that it would instead be better to confine myself to making some general reflections on knowledge representation given by imprecise information using fuzzy sets; reflections which have been suggested to me by some words in the following articles such as: graded notions, fuzzy objects, uncertainty, fuzzy implications, fuzzy inference, empty intersection, etc.

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