Recommendation Assistant System for Social Networks and Search Services Based on Population Filtering Algorithm

DOI

10.2991/assehr.k.200723.061How to use a DOI?

Keywords

recommendation system, collaborative and content filtering, population algorithm

Abstract

The authors present a hybrid model of a recommender system. The system includes the characteristics of collaborative and content filtering. Also, the article describes a population filtering algorithm and the architecture of a recommendation system based on it. The results of experimental studies on an array of benchmarks and an estimation of filtering efficiency based on a hybrid model and a population algorithm are presented. The results are compared with the traditional method of collaborative filtering using the Pearson correlation coefficient.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Sergey Rodzin
AU  - Victoria Bova
AU  - Yuri Kravchenko
AU  - Olga Rodzina
AU  - Lada Rodzina
AU  - Elmar Kuliev
PY  - 2020
DA  - 2020/07/23
TI  - Recommendation Assistant System for Social Networks and Search Services Based on Population Filtering Algorithm
BT  - Proceedings of the International Scientific Conference on Philosophy of Education, Law and Science in the Era of Globalization (PELSEG 2020)
PB  - Atlantis Press
SP  - 291
EP  - 295
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.200723.061
DO  - 10.2991/assehr.k.200723.061
ID  - Rodzin2020
ER  -