A recommender system based on a generic contextual advertising approach

Contextual advertising and automatic recommendation are emerging fields deeply studied by researchers in information retrieval. So far, these fields have been separately investigated and several solutions have been independently proposed in the literature. Nevertheless, in our view, there are common issues that drive us to think that systems devised to solve one of the task above could be simply re-adapted to solve the other. In this paper, we propose a novel recommendation system based on a generic solution typically adopted to solve contextual advertising tasks. Experimental results highlight the effectiveness of the proposed approach.