Multi-objective genetic algorithms based automated clustering for fuzzy association rules mining

Researchers realized the importance of integrating fuzziness into association rules mining in databases with binary and quantitative attributes. However, most of the earlier algorithms proposed for fuzzy association rules mining either assume that fuzzy sets are given or employ a clustering algorith...

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Veröffentlicht in:	Journal of intelligent information systems Jg. 31; H. 3; S. 243 - 264
Hauptverfasser:	Alhajj, Reda, Kaya, Mehmet
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Boston Springer US 01.12.2008 Springer Nature B.V
Schlagworte:	Artificial Intelligence Associations Automation Chromosomes Clustering Computer Science Data mining Data Structures and Information Theory Fuzzy logic Fuzzy sets Genetic algorithms Information Storage and Retrieval IT in Business Natural Language Processing (NLP) Optimization Set theory Studies Multi-objective genetic algorithms CURE Fuzziness Automated clustering Data mining Fuzzy association rules
ISSN:	0925-9902, 1573-7675
Online-Zugang:	Volltext
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