Fuzziness in Information Systems

How to Deal with Crisp and Fuzzy Data in Selection, Classification, and Summarization

  • Miroslav┬áHudec

Table of contents

  1. Front Matter
    Pages i-xxii
  2. Miroslav Hudec
    Pages 1-32
  3. Miroslav Hudec
    Pages 33-66
  4. Miroslav Hudec
    Pages 67-99
  5. Miroslav Hudec
    Pages 101-137
  6. Miroslav Hudec
    Pages 139-176
  7. Miroslav Hudec
    Pages 177-181
  8. Back Matter
    Pages 183-198

About this book


This book is an essential contribution to the description of fuzziness in information systems. Usually users want to retrieve data or summarized information from a database and are interested in classifying it or building rule-based systems on it. But they are often not aware of the nature of this data and/or are unable to determine clear search criteria. The book examines theoretical and practical approaches to fuzziness in information systems based on statistical data related to territorial units.

Chapter 1 discusses the theory of fuzzy sets and fuzzy logic to enable readers to understand the information presented in the book. Chapter 2 is devoted to flexible queries and includes issues like constructing fuzzy sets for query conditions, and aggregation operators for commutative and non-commutative conditions, while Chapter 3 focuses on linguistic summaries. Chapter 4 presents fuzzy logic control architecture adjusted specifically for the aims of business and governmental agencies, and shows fuzzy rules and procedures for solving inference tasks. Chapter 5 covers the fuzzification of classical relational databases with an emphasis on storing fuzzy data in classical relational databases in such a way that existing data and normal forms are not affected. This book also examines practical aspects of user-friendly interfaces for storing, updating, querying and summarizing. Lastly, Chapter 6 briefly discusses possible integration of fuzzy queries, summarization and inference related to crisp and fuzzy databases.

The main target audience of the book is researchers and students working in the fields of data analysis, database design and business intelligence. As it does not go too deeply into the foundation and mathematical theory of fuzzy logic and relational algebra, it is also of interest to advanced professionals developing tailored applications based on fuzzy sets.


Vagueness and fuzzy logic Artificial Intelligence Multilingual text search Multilingual summaries Logic and databases Database query processing and optimization Relational database models Probabilistic inference problems

Authors and affiliations

  • Miroslav┬áHudec
    • 1
  1. 1.Faculty of Economic InformaticsUniversity of Economics in Bratisla Faculty of Economic InformaticsBratislavaSlovakia

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-42516-0
  • Online ISBN 978-3-319-42518-4
  • Buy this book on publisher's site