Towards a Compound Remote Associate Test Solver based on Language Data

The Remote Associate Test (RAT) is generally used for measuring creativity in humans. In this paper, the initial parts of a creative cognitive problem- solving framework are implemented to solve the RAT automatically using a knowledge base of language data extracted from the Corpus of Contemporary American English. The results provided by the computational RAT are compared to those obtained in previous RATs carried out to human participants in order to hyphotesize on an associationist creative cognition paradigm.