Using a Recommender System to Help the Technology Transfer Office Staff to Disseminate Selective Information

Recommender systems evaluate and filter the great amount of information available on the Web, so they could be used to help users in their access processes to relevant information. In the literature we can find a lot of approaches for generating personalized recommendations. Hybrid recommender systems combine in different ways several approaches, so these recommendation strategies represent a promising solution for multiple applications. In this paper we propose a hybrid fuzzy linguistic recommender system to help the Technology Transfer Office staff in the dissemination of research resources interesting for the users. The system recommends users both specialized and complementary research resources and additionally, it discovers potential collaboration possibilities in order to form multidisciplinary working groups.