A Big Data Approach to Computational Creativity
Abstract
Computational creativity is an emerging branch of artificial intelligence that places computers in the center of the creative process. Broadly, creativity involves a generative step to produce many ideas and a selective step to determine the ones that are the best. Many previous attempts at computational creativity, however, have not been able to achieve a valid selective step. This work shows how bringing data sources from the creative domain and from hedonic psychophysics together with big data analytics techniques can overcome this shortcoming to yield a system that can produce novel and high-quality creative artifacts. Our data-driven approach is demonstrated through a computational creativity system for culinary recipes and menus we developed and deployed, which can operate either autonomously or semi-autonomously with human interaction. We also comment on the volume, velocity, variety, and veracity of data in computational creativity.
Cite
@article{arxiv.1311.1213,
title = {A Big Data Approach to Computational Creativity},
author = {Lav R. Varshney and Florian Pinel and Kush R. Varshney and Debarun Bhattacharjya and Angela Schoergendorfer and Yi-Min Chee},
journal= {arXiv preprint arXiv:1311.1213},
year = {2013}
}