WordNet-based user profiles for neighborhood formation in hybrid recommender systems

Recommender systems help to reduce information overload and provide customized information access for targeted domains. Such systems take input from users and, based on their needs and preferences, provide personalized advices that help people to filter useful information. Collaborative filtering and content-based filtering are the most widely recommendation techniques adopted to date. The paper presents a new hybrid recommendation technique based on the combination of classic collaborative filtering and user profiles inferred using content-based methods.