By
Awais Ali
FA20-CSE-009
Department of Computer System Engineering
Mirpur University of Science and Technology
December, 2022
“A Literature Overview of Fuzzy Database Models”
Summary:-
Fuzzy database models are a type of database model that use fuzzy logic to
represent and manipulate data. Fuzzy logic allows for approximate rather than
exact reasoning, which can be useful in situations where the data is imprecise or
incomplete.
Fuzzy database models have been studied extensively in the literature, and many
different approaches to their design and implementation have been proposed. Some
of the key features of fuzzy database models include the ability to handle
uncertainty and imprecision in data, the use of fuzzy set theory to represent data,
and the ability to perform approximate queries and reasoning on the data.
One of the key advantages of fuzzy database models is their ability to handle
imprecise or incomplete data. Traditional database models are based on classical
logic, which only allows for exact reasoning and cannot deal with uncertainty or
imprecision. By contrast, fuzzy database models can represent data using fuzzy
sets, which allow for a more flexible and approximate representation of data. This
can be useful in situations where the data is uncertain or incomplete, and where
traditional database models may not be able to accurately represent the data.
Another key advantage of fuzzy database models is their ability to perform
approximate queries and reasoning on the data. In traditional database models,
queries and reasoning are performed using exact, classical logic, which can be
inefficient or infeasible in situations where the data is uncertain or imprecise. By
contrast, fuzzy database models can perform approximate queries and reasoning
using fuzzy logic, which allows for more efficient and effective processing of the
data.
Overall, the literature on fuzzy database models is extensive, and there are many
different approaches to their design and implementation. These models have been
applied to a wide range of real-world problems, and have been shown to be
effective in dealing with uncertainty and imprecision in data.
1 REFERENCES
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Ma, Z.M.. (2006). A Literature Overview of Fuzzy Database Modeling.
Intelligent Databases: Technologies and Applications. 10.4018/978-159904-120-9.ch008.
https://chat.openai.com/chat
O. Bahar and A. Yazici, “Normalization and lossless join decomposition of
similarity-based fuzzy relational databases,” International Journal of
Intelligent Systems, Vol. 19, 2004, pp. 885-917
T. K. Bhattacharjee and A. K. Mazumdar, “Axiomatisation of fuzzy
multivalued dependencies in a fuzzy relational data model,” Fuzzy Sets
and Systems, Vol. 96, 1998