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We present iTag, a personalized tag recommendation system for blogs. iTag improves on the state-of-the-art in tag recommendation systems in two ways. First, iTag has much higher p...
Providing justification to a recommendation gives credibility to a recommender system. Some recommender systems (Amazon.com etc.) try to explain their recommendations, in an eff...
This work addresses a particular kind of cross domain personalization task consisting of selecting simultaneously two items in two different domains and recommending them togethe...
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...
Robustness analysis research has shown that conventional memory-based recommender systems are very susceptible to malicious profile-injection attacks. A number of attack models h...
Critiquing-based recommenders do not require users to state all of their preferences upfront or rate a set of previously experienced products. Compared to other types of recommend...
Collaborative tagging applications have become a popular tool allowing Internet users to manage online resources with tags. Most collaborative tagging applications permit unsuperv...
Jonathan Gemmell, Maryam Ramezani, Thomas Schimole...