Most recommendation methods (e.g., collaborative filtering) consist of (1) a computationally intense offline phase that computes a recommender model based on users’ opinions o...
Justin J. Levandoski, Mohamed Sarwat, Mohamed F. M...
We propose a model for user purchase behavior in online stores that provide recommendation services. We model the purchase probability given recommendations for each user based on...
The problem of building Recommender Systems has attracted considerable attention in recent years, but most recommender systems are designed for recommending items for individuals....
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-...
Acquiring relevant information to keep user’s preferences up-to-date is crucial in recommender systems in order to close the cycle of recommendations. Ambient Intelligence is a s...