# A Big Data Approach to Computational Creativity

arXiv: https://arxiv.org/abs/1311.1213 · HTML: https://mlsanity.com/paper/1311.1213/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Nov 2013.

## Built on by (most cited first, 3 of 3)

- [LLaVA-Chef: A Multi-modal Generative Model for Food Recipes](https://mlsanity.com/paper/2408.16889/) (2024)
- [Predicting New Research Directions in Materials Science using Large Language Models and Concept Graphs](https://mlsanity.com/paper/2506.16824/) (2025)
- [Monte Carlo Tree Search for Recipe Generation using GPT-2](https://mlsanity.com/paper/2401.05199/) (2024)

## Abstract (arXiv)

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.