Integrated concept blending with vector space models

The concept-blender input is then conformed by a set of n-nouns. All input members are read and substituted by their corresponding vectors. Then, a semantic space analysis including a filtering and ranking process is carried out to deploy a list of target words. A test set of 50 concepts was created in order to evaluate the system's performance. A group of 30 evaluators found our integrated concept blending model to provide better results for finding an adequate word for the provided set of concepts.