Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Big Data Approach to Computational Creativity   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.

5
The categories of this paper are: gr-qc
23
The categories of this paper are: solv-int
17
The categories of this paper are: q-fin
0
The categories of this paper are: hep-ph
22
The categories of this paper are: chao-dyn
2
The categories of this paper are: math
25
The categories of this paper are: patt-sol
27
The categories of this paper are: comp-gas
11
The categories of this paper are: hep-lat
26
The categories of this paper are: bayes-an
32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat
9
The categories of this paper are: nlin