  Human creativity is often described as the mental process of combining
associative elements into a new form, but emerging computational creativity
algorithms may not operate in this manner. Here we develop an inverse problem
formulation to deconstruct the products of combinatorial and compositional
creativity into associative chains as a form of post-hoc interpretation that
matches the human creative process. In particular, our formulation is
structured as solving a traveling salesman problem through a knowledge graph of
associative elements. We demonstrate our approach using an example in
explaining culinary computational creativity where there is an explicit
semantic structure, and two examples in language generation where we either
extract explicit concepts that map to a knowledge graph or we consider
distances in a word embedding space. We close by casting the length of an
optimal traveling salesman path as a measure of novelty in creativity.
