Title
Computational Creativity Support: Using Algorithms And Machine Learning To Help People Be More Creative
Keywords
Creativity support tools; Data mining; Machine learning; Signal processing
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.
Publication Date
9-22-2009
Publication Title
Conference on Human Factors in Computing Systems - Proceedings
Number of Pages
4733-4736
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1145/1520340.1520728
Copyright Status
Unknown
Socpus ID
70349182085 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/70349182085
STARS Citation
Morris, Dan and Secretan, Jimmy, "Computational Creativity Support: Using Algorithms And Machine Learning To Help People Be More Creative" (2009). Scopus Export 2000s. 12082.
https://stars.library.ucf.edu/scopus2000/12082