A method for audience extending in programmatic advertising by using parsimonious generalization of user segments

Abstract

We propose a novel method for efficient target audience augmentation in programmatic digital advertising. This method utilizes a novel ParGenFS algorithm for most adequate generalization in taxonomies which was developed by the authors in a joint work. The ParGenFS extends user segments by parsimoniously lifting them off-line as a fuzzy set over IAB content taxonomy into a higher rank ‘head subject’. This algorithm was initially intended as an intelligent information retrieval tool. Here it is applied to a very different task of targeted advertisement as an effective tool for augmenting audiences.