A Type-2 Fuzzy Approach to Linguistic Summarization of Data

This paper introduces an application of type-2 fuzzy sets in data linguistic summarization. The original approach by Yager (1982) based on representing natural language statements via type-1, i.e., the Zadeh fuzzy sets, is generalized with type-2 fuzzy sets applied as models of linguistically expres...

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Bibliographic Details
Published in:IEEE transactions on fuzzy systems 2008-02, Vol.16 (1), p.198-212
Main Author: Niewiadomski, A.
Format: Article
Language:English
Subjects:
Anthropometry
Data mining
Fuzzy
Fuzzy logic
Fuzzy set theory
Fuzzy sets
Humans
knowledge extraction
linguistic summarization of databases
Linguistics
Materials handling
Mathematical models
Messages
Natural languages
Process control
Prototypes
Temperature measurement
type-2 fuzzy quantifiers
type-2 fuzzy sets
type-2 linguistic summaries
type-2 linguistic variables
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Summary:This paper introduces an application of type-2 fuzzy sets in data linguistic summarization. The original approach by Yager (1982) based on representing natural language statements via type-1, i.e., the Zadeh fuzzy sets, is generalized with type-2 fuzzy sets applied as models of linguistically expressed quantities and/or properties of objects. Type-2 sets extend the known summarization procedures by handling fuzzy values stored in databases, and allow to represent a linguistic term via a few different membership functions (e.g., provided by different experts), which makes the method more general and human-consistent. Furthermore, quality measures for type-2 summaries are discussed in order to evaluate the informativeness of the messages generated. Finally, two prototype applications are presented and the success of the new method is discussed.
ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2007.902025