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

Jejunum

書目名稱Computational Creativity影響因子(影響力)




書目名稱Computational Creativity影響因子(影響力)學科排名




書目名稱Computational Creativity網(wǎng)絡公開度




書目名稱Computational Creativity網(wǎng)絡公開度學科排名




書目名稱Computational Creativity被引頻次




書目名稱Computational Creativity被引頻次學科排名




書目名稱Computational Creativity年度引用




書目名稱Computational Creativity年度引用學科排名




書目名稱Computational Creativity讀者反饋




書目名稱Computational Creativity讀者反饋學科排名

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

助記

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.

助記

公豬

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.