Seeking Divisions of Domains on Semantic Networks by Evolutionary Bridging

Computational Creativity systems based on Conceptual Blending (CB) and Bisociation theories operate on input knowledge to reveal seemingly unrelated information. The input spaces or domains can be of various sources and contain vast amounts of knowledge. It is central a process that selects useful building blocks of semantic data that does not narrow the search space of the creative algorithm. It is also vital that the data selection process is of high performance in order to handle a large knowledge base in a useful time. With those objectives in mind, we propose an evolutionary high performance algorithm that extracts two semantic sub-graphs from a knowledge base to be used as building blocks in computational blending processes.