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Computational creativity support: using algorithms and machine learning to help people be more creative


ZotWeb	paper-conference
Src Url	Morris, Secretan (2009)

Abstract

The emergence of computers as a core component of creative processes, coupled with recent advances in machine-learning, signal-processing, and algorithmic techniques for manipulating creative media, offers tremendous potential for building end-user creativity-support tools. However, the scientific community making advances in relevant algorithmic techniques is not, in many cases, the same community that is currently making advances in the design, evaluation, and user-experience aspects of creativity support. The primary objective of this workshop is thus to bring together participants from diverse backgrounds in the HCI, design, art, machine-learning, and algorithms communities to facilitate the advancement of novel creativity support tools.

Annotations

Computational creativity support using algorithms

The emergence of computers as a core component of creative processe

advances in machine-learnin

Keywords

Outils de support à la créativité, exploration de données (data-mining)

is intended to bring together participants from multiple communities who share an interest in creativity suppor

Identify potential collaborations among the communities represented her

Facilitate discussion of the tools and methodologies

Facilitate discussion of the implementation and evaluation challenge

Conclusion

This workshop aims to bring together diverse communities to foster the advancement of creativity support tools, and we expect that it will be a unique opportunity to exchange tools and experiences from communities outside your own. If you are active in this space, or have a strong personal interest in this space and work on relevant tools or methodologies, consider submitting to Computational Creativity Support 200

References

Shneiderman, B., “Creativity Support Tools: Accelerating Discovery and Innovation,” Communications of the ACM, Vol. 50, No. 12, 2007

Howe, D.C. RiTa: Creativity Support for Generative Literature. Proc Generative Art Intl Cof, 2008.

Keefe, D.F., Acevedo, D., Miles, J., Drury, F., Swartz, S.M., Laidlaw, D.H. Scientific Sketching for Collaborative VR Visualization design. IEEE Trans Visualization Comp Graph, 14(4):835-847, 200

Sheppard, R.M, Kamali, M., Rivas, R., Tamai, M., Yang, Z., Wu, W., Nahrstedt, K. Advancing Interactive Collaborative Mediums through Tele- immersive Dance (TED): a Symbiotic Creativity and Design Environment for Art and Computer Science. ACM Intl Conf on Multimedia (MM'08), 2008.

Citer: (Morris & Secretan, 2009)

FTag: Morris-Secretan-2009

APA7: Morris, D., & Secretan, J. (2009). Computational creativity support: Using algorithms and machine learning to help people be more creative. CHI ’09 Extended Abstracts on Human Factors in Computing Systems, 4733–4736. https://doi.org/10.1145/1520340.1520728