A Framework for Use of Imprecise Categorization in Developing Intelligent Systems

A Framework for Use of Imprecise Categorization in Developing Intelligent Systems

In this paper, we develop characterizations of the properties of categories. We introduce an approach to representing imprecise hierarchies based on the idea of fragmentation. In the case of fuzzy categories, measures of how well fuzzy categorization satisfies the concept of a partitioning for such...

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Veröffentlicht in:IEEE transactions on fuzzy systems 2010-04, Vol.18 (2), p.348-361
Hauptverfasser: Petry, F.E., Yager, R.R.
Format: Artikel
Sprache:eng
Schlagworte:
Categories
Clustering algorithms
concept hierarchy
Context
Data mining
Formulations
fragmentation
Fuzzy
Fuzzy logic
Fuzzy set theory
Fuzzy systems
Hierarchies
Humans
Intelligent systems
Laboratories
Machine intelligence
Partitioning
partitions
Pattern recognition
Prototypes
Statistics
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Beschreibung
Zusammenfassung:In this paper, we develop characterizations of the properties of categories. We introduce an approach to representing imprecise hierarchies based on the idea of fragmentation. In the case of fuzzy categories, measures of how well fuzzy categorization satisfies the concept of a partitioning for such categories are developed. Finally, issues that are involved in the formulation of fuzzy categorization of a domain using approaches based on the use of prototypes are considered.
ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2010.2041782