Titlebook: Computational Creativity; The Philosophy and E Tony Veale,F. Amílcar Cardoso Book 2019 Springer Nature Switzerland AG 2019 Artificial Intel

Jejunum

书目名称Computational Creativity影响因子(影响力)




书目名称Computational Creativity影响因子(影响力)学科排名




书目名称Computational Creativity网络公开度




书目名称Computational Creativity网络公开度学科排名




书目名称Computational Creativity被引频次




书目名称Computational Creativity被引频次学科排名




书目名称Computational Creativity年度引用




书目名称Computational Creativity年度引用学科排名




书目名称Computational Creativity读者反馈




书目名称Computational Creativity读者反馈学科排名

勾引

Myocyte

From Conceptual Mash-ups to Badass Blends: A Robust Computational Model of Conceptual Blending,to ourselves and to others every day. By acquiring its world knowledge from the questions of others, a computer can eventually learn to pose introspective questions of its own, in the service of its own creative ..

洞穴

Breaking the Mould An Evolutionary Quest for Innovation Through Style Change,s, which includes retraining the classifier, sets the system into a permanent quest for novelty and innovation. The experimental results obtained across several iterations are presented and analysed, showing the ability of the system to consistently produce novel imagery and to identify atypical images.

刺激

助记

https://doi.org/10.1007/978-3-030-16924-4nse knowledge (CSK) that includes social features is a useful tool in this endeavour. This chapter describes how MEXICA, a plot generator, exploits such social CSK to generate narratives avoiding the use of predefined story structures. The results suggest that this is a promising approach.

助记

公猪

David I. Levy,K. Kitz,M. Killer,B. Richlingals. We base this on cognitive science research that shows this behaviour during creative design in humans. We present formal notation for a simple model of expectation, and give examples from our implementations in the domains of product design and culinary creativity.

integral

LATHE

Bisociative Knowledge Discovery for Cross-domain Literature Mining,ext mining, addressing cross-domain literature-based discovery. Two approaches are briefly outlined: the CrossBee approach to cross-domain bridgingterm detection, and the OntoGen approach to bridging-term detection through outlier document exploration.