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Data mining and machine learning in computational creativity

delete2015-10-02
delete29
PRE
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H
Hannu Toivonen *
O
Oskar Gross
DOI:10.1002/widm.1170delete
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Abstract

Abstract

En 中文
Creative machines are an old idea, but only recently computational creativity has established itself as a research field with its own identity and research agenda. The goal of computational creativity research is to model, simulate, or enhance creativity using computational methods. Data mining and machine learning can be used in a number of ways to help computers learn how to be creative, such as learning to generate new artifacts or to evaluate various qualities of newly generated artifacts. In this review paper, we give an overview of research in computational creativity with a focus on the roles that data mining and machine learning have had and could have in creative systems. WIREs Data Mining Knowl Discov 2015, 5:265-275. doi: 10.1002/widm.1170 For further resources related to this article, please visit the .
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Journal

Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery cover
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery
IF:
11.7
Papers:
532
Citations:
5.3K

Organization

U
university of helsinki
Scholars:
4.1W
Papers: 3.6W
Citations: 51