Florián, Beatriz E.Valencia, María EugeniaRodríguez, Paola J.Millán, MarthaGaona, Carlos M.Carrillo, Javier E.Ciprián, Mauricio
Information retrieval (IR) deals with representation, organization, and storage of information. IR should provide the user with an easy access to the information in which he or she is interested. However, characterization of the user information needs is a complex problem. Usually, a full description of the user information needs cannot be made dir...
Memory-based collaborative filtering is the state-of-the-art method in recommender systems and has proven to be successful in various applications. In this paper we develop novel memory-based methods that incorporate the level of a user credit instead of using similarity between users. The user credit is the degree of one's rating reliability that ...
Memory-based collaborative filtering (CF) makes recommendations based on a collection of user preferences for items. The idea underlying this approach is that the interests of an active user will more likely coincide with those of users who share similar preferences to the active user. Hence, the choice and computation of a similarity measure betwe...
Despite the existence of dierent methods, including data mining techniques, available to be used in recommender systems, such systems still contain numerous limitations. They are in a constant need for personalization in order to make effective suggestions and to provide valuable information of items available. A way to reach such personalization i...
Matrix factorization with trace norm regularization is a popular approach to matrix completion and collaborative filtering. When entries of the matrix are sampled non-uniformly (which is the case for collaborative prediction), a properly weighted correction to the trace norm regularization is known to improve the performance dramatically. While the...
Modern technology has drastically changed the way we interact and consume information. For example, online social platforms allow for seamless communication exchanges at an unprecedented scale. However, we are still bounded by cognitive and temporal constraints. Our attention is limited and extremely valuable. Algorithmic personalisation has become...