Premium
Data mining and machine learning in computational creativity
Author(s) -
Toivonen Hannu,
Gross Oskar
Publication year - 2015
Publication title -
wiley interdisciplinary reviews: data mining and knowledge discovery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.506
H-Index - 47
eISSN - 1942-4795
pISSN - 1942-4787
DOI - 10.1002/widm.1170
Subject(s) - creativity , computational creativity , computer science , field (mathematics) , artificial intelligence , machine learning , computational model , data science , focus (optics) , identity (music) , creativity technique , psychology , social psychology , physics , mathematics , acoustics , pure mathematics , optics
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 This article is categorized under: Application Areas > Science and Technology Application Areas > Society and Culture