A semantic approach to avoiding fake neighborhhoods in collaborative recommmendation of coupons through Digital TV

Consumers are flooded with amounts of discount coupons, oftentimes for products that are far from their interests. This marketing custom is already rising in Internet, and it is imminent in Digital TV. But the computing capability of these media permits to alleviate this problem by means of recommender systems, very useful tools in application domains that suffer from information overload. However, current recommender systems overlook the diversity of products and services available in the market, which gives rise to form fake neighborhoods in collaborative filtering strategies. In this paper, we apply semantic reasoning techniques to solve this problem.