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Fuzziness in Information Systems How to Deal with Crisp and Fuzzy Data in Selection Classification and Summarization

Release: Fuzziness.in.Information.Systems.How.to.Deal.with.Crisp.and.Fuzzy.Data.in.Selection.Classification.and.Summarization

  • Sprache: Englisch
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Fuzziness in Information Systems: How to Deal with Crisp
and Fuzzy Data in Selection, Classification, and
Summarization by Miroslav Hudec
English | 2016 | ISBN: 3319425161 | 198 pages | PDF | 5
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.
Sach und Fachbuecher English

Fuzziness in Information Systems How to Deal with Crisp and Fuzzy Data in Selection Classification and Summarization


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