Maria Rafalak, Janusz Granat, Andrzej Piotr Wierzbicki


This paper presents a novel approach for user classification exploiting multicriteria
analysis. This method is based on measuring the distance between an
observation and its respective Pareto front. The obtained results show that the
combination of the standard KNN classification and the distance from Pareto
fronts gives satisfactory classification accuracy – higher than the accuracy obtained
for each of these methods applied separately. Conclusions from this
study may be applied in recommender systems where the proposed method
can be implemented as the part of the collaborative filtering algorithm.


recommender systems, multi-criteria analysis, user profiling

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