We investigate two recommendation approaches suitable for online multimedia sharing services. Our first approach, UserRank, recommends items by global interestingness irrespective...
The open nature of collaborative recommender systems allows attackers who inject biased profile data to have a significant impact on the recommendations produced. Standard memory-...
In this paper we present a hybrid recommendation system that combines ontological knowledge with content-extracted linguistic information, derived from pre-trained lexical graphs,...
Dorothea Tsatsou, Fotis Menemenis, Ioannis Kompats...
Recommender systems are used by an increasing number of e-commerce websites to help the customers to find suitable products from a large database. One of the most popular techniqu...
Stefan Hauger, Karen H. L. Tso, Lars Schmidt-Thiem...
We consider the problem of recommending the best set of k items when there is an inherent ordering between items, expressed as a set of prerequisites (e.g., the course ‘Real Ana...