APPLICATION OF MULTI-CRITERIA ANALYSIS BASED ON INDIVIDUAL PSYCHOLOGICAL PROFILE FOR RECOMMENDER SYSTEMS

Maria Rafalak , Janusz Granat , Andrzej Wierzbicki

Abstract

This paper presents a novel approach for user classification exploiting multi- criteria 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 ob- tained 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.
Author Maria Rafalak
Maria Rafalak,,
-
, Janusz Granat (FEIT / AK) - Instytut Łączności PIB (IŁ PIB) [Instytut Łączności PIB (IŁ PIB)]
Janusz Granat,,
- The Institute of Control and Computation Engineering
- Instytut Łączności PIB
, Andrzej Wierzbicki (FEIT / AK) - Instytut Łączności PIB (IŁ PIB) [Instytut Łączności PIB (IŁ PIB)]
Andrzej Wierzbicki,,
- The Institute of Control and Computation Engineering
- Instytut Łączności PIB
Journal seriesComputer Science, [Computer Science], ISSN 1508-2806, e-ISSN 2300-7036
Issue year2016
Vol17
No4
Pages503-517
Publication size in sheets0.3
Keywords in Englishrecommender systems, multi-criteria analysis, user profiling
DOIDOI:10.7494/csci.2016.17.4.503
URL https://journals.agh.edu.pl/csci/article/view/1862/1586
Languageen angielski
Score (nominal)12
Score sourcejournalList
ScoreMinisterial score = 12.0, 14-02-2020, ArticleFromJournal
Ministerial score (2013-2016) = 12.0, 14-02-2020, ArticleFromJournal
Publication indicators WoS Citations = 0
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