Overview
- Explains the application of fuzzy approaches for classical relational databases and information systems
- Details important application aspects like fuzzy queries, fuzzy inference, and linguistic summaries
- Includes a brief introduction to fuzzy sets and fuzzy logic
- Includes supplementary material: sn.pub/extras
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Table of contents (6 chapters)
Keywords
About this book
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.
Authors and Affiliations
About the author
Miroslav Hudec is researcher and teacher at the University of Economics in Bratislava, Slovakia. His research activities have been focused on information systems in official statistics and theory and applications of fuzzy logic, data mining and operations research. He is the author of approximately 45 scientific papers, a member of the program committee of several related international conferences and (currently) an editorial board member for Applied Soft Computing. In addition, he was the representative of Slovakia in the UNECE/Eurostat/OECD Conference on the Management of Statistical Information Systems from 2005 to 2009 and again in 2013.
Bibliographic Information
Book Title: Fuzziness in Information Systems
Book Subtitle: How to Deal with Crisp and Fuzzy Data in Selection, Classification, and Summarization
Authors: Miroslav Hudec
DOI: https://doi.org/10.1007/978-3-319-42518-4
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Hardcover ISBN: 978-3-319-42516-0Published: 07 October 2016
Softcover ISBN: 978-3-319-82598-4Published: 22 April 2018
eBook ISBN: 978-3-319-42518-4Published: 28 September 2016
Edition Number: 1
Number of Pages: XXII, 198
Number of Illustrations: 91 b/w illustrations
Topics: Data Mining and Knowledge Discovery, Computational Intelligence, Information Systems Applications (incl. Internet), Mathematical Logic and Formal Languages, Artificial Intelligence