PROFILE LEARNER – This module collects data representative of the user preferences and tries to generalize this data, in order to construct the user profile. Usually, the generalization strategy is realized through machine learning techniques
[61], which are able to infer a model of user interests starting from items liked or
disliked in the past. For instance, the PROFILE LEARNER of a Web page recommender can implement a relevance feedback method [75] in which the learning
technique combines vectors of positive and negative examples into a prototype
vector representing the user profile. Training examples are Web pages on which
a positive or negative feedback has been provided by the user;