Recommending Products with a Fuzzy Classification
Henrik Stormer, Nicolas Werro, Daniel Risch · Institutional Repository (IHS Vienna) · 2006
Recommender systems are becoming more and more important for online shop systems. A recommender system suggests potentially interesting products to customers. However, shop administrators typically want to influence the recommendations due to the fact that not all products have the same value for the shop. The shop administrators therefore prefer to recommend products with a higher product value. This paper starts by suggesting a fuzzy classification to precisely calculate the value of the products. Afterwards the calculated product values can be utilized to influence a recommender system to suggest products with a higher value more often.