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A Network Centrality Method for the Rating Problem
We propose a new method for aggregating the information of multiple users rating multiple items. Our approach is based on the network relations induced between items by the rating activity of the users. Our method correlates better than the simple average with respect to the original rankings of the...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4382193/ https://www.ncbi.nlm.nih.gov/pubmed/25830502 http://dx.doi.org/10.1371/journal.pone.0120247 |
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author | Li, Yongli Pin, Paolo Wu, Chong |
author_facet | Li, Yongli Pin, Paolo Wu, Chong |
author_sort | Li, Yongli |
collection | PubMed |
description | We propose a new method for aggregating the information of multiple users rating multiple items. Our approach is based on the network relations induced between items by the rating activity of the users. Our method correlates better than the simple average with respect to the original rankings of the users, and besides, it is computationally more efficient than other methods proposed in the literature. Moreover, our method is able to discount the information that would be obtained adding to the system additional users with a systematically biased rating activity. |
format | Online Article Text |
id | pubmed-4382193 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-43821932015-04-09 A Network Centrality Method for the Rating Problem Li, Yongli Pin, Paolo Wu, Chong PLoS One Research Article We propose a new method for aggregating the information of multiple users rating multiple items. Our approach is based on the network relations induced between items by the rating activity of the users. Our method correlates better than the simple average with respect to the original rankings of the users, and besides, it is computationally more efficient than other methods proposed in the literature. Moreover, our method is able to discount the information that would be obtained adding to the system additional users with a systematically biased rating activity. Public Library of Science 2015-04-01 /pmc/articles/PMC4382193/ /pubmed/25830502 http://dx.doi.org/10.1371/journal.pone.0120247 Text en © 2015 Li et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Li, Yongli Pin, Paolo Wu, Chong A Network Centrality Method for the Rating Problem |
title | A Network Centrality Method for the Rating Problem |
title_full | A Network Centrality Method for the Rating Problem |
title_fullStr | A Network Centrality Method for the Rating Problem |
title_full_unstemmed | A Network Centrality Method for the Rating Problem |
title_short | A Network Centrality Method for the Rating Problem |
title_sort | network centrality method for the rating problem |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4382193/ https://www.ncbi.nlm.nih.gov/pubmed/25830502 http://dx.doi.org/10.1371/journal.pone.0120247 |
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