A collaborative filtering system at an e-commerce site or similar service uses data about aggregate user behavior to make recommendations tailored to specific user interests. We d...
Collaborative filtering (CF) is valuable in e-commerce, and for direct recommendations for music, movies, news etc. But today's systems have several disadvantages, including ...
CAFE (Collaborative Agents for Filtering E-mails) is a multi-agent system to collaboratively filter spam from users’ mail stream. CAFE associates a proxy agent with each user, a...
Within the task of collaborative filtering two challenges for computing conditional probabilities exist. First, the amount of training data available is typically sparse with resp...
Collaborative filtering (CF) recommender systems are very popular and successful in commercial application fields. However, robustness analysis research has shown that conventional...