Prediction of new user preferences with filtering techniques

Abstract

Collaborative filtering techniques are often used to predict the unknown preferences of a new user by applying rules derived from the known preferences of a group of users. In the literature users having high correlation with a large number of other users are referred to as 'white sheeps', while those that express preferences which do not fall into any known to the system group are called 'grey sheeps'. Thus predictions for the latter type users are often inaccurate. To overcome this problem we propose application of residuated lattices. © 2014 Springer-Verlag Berlin Heidelberg.