Collaborative filtering techniques have been successfully employed in recommender systems in order to help users deal with information overload by making high quality personalize...
Paul-Alexandru Chirita, Wolfgang Nejdl, Cristian Z...
We present an approach to learning the personal preferences of individual users directly from example images. The target application is computer assisted search of partners in onl...
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...
Abstract--Although temporal context may significantly affect the popularity of items and user preference over items, traditional information filtering techniques such as recommende...
Online information services have grown too large for users to navigate without the help of automated tools such as collaborative filtering, which makes recommendations to users ba...