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Behavior Based Social Dimensions Extraction for Multi-Label Classification
Classification based on social dimensions is commonly used to handle the multi-label classification task in heterogeneous networks. However, traditional methods, which mostly rely on the community detection algorithms to extract the latent social dimensions, produce unsatisfactory performance when c...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4822808/ https://www.ncbi.nlm.nih.gov/pubmed/27049849 http://dx.doi.org/10.1371/journal.pone.0152857 |
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author | Li, Le Xu, Junyi Xiao, Weidong Ge, Bin |
author_facet | Li, Le Xu, Junyi Xiao, Weidong Ge, Bin |
author_sort | Li, Le |
collection | PubMed |
description | Classification based on social dimensions is commonly used to handle the multi-label classification task in heterogeneous networks. However, traditional methods, which mostly rely on the community detection algorithms to extract the latent social dimensions, produce unsatisfactory performance when community detection algorithms fail. In this paper, we propose a novel behavior based social dimensions extraction method to improve the classification performance in multi-label heterogeneous networks. In our method, nodes’ behavior features, instead of community memberships, are used to extract social dimensions. By introducing Latent Dirichlet Allocation (LDA) to model the network generation process, nodes’ connection behaviors with different communities can be extracted accurately, which are applied as latent social dimensions for classification. Experiments on various public datasets reveal that the proposed method can obtain satisfactory classification results in comparison to other state-of-the-art methods on smaller social dimensions. |
format | Online Article Text |
id | pubmed-4822808 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-48228082016-04-22 Behavior Based Social Dimensions Extraction for Multi-Label Classification Li, Le Xu, Junyi Xiao, Weidong Ge, Bin PLoS One Research Article Classification based on social dimensions is commonly used to handle the multi-label classification task in heterogeneous networks. However, traditional methods, which mostly rely on the community detection algorithms to extract the latent social dimensions, produce unsatisfactory performance when community detection algorithms fail. In this paper, we propose a novel behavior based social dimensions extraction method to improve the classification performance in multi-label heterogeneous networks. In our method, nodes’ behavior features, instead of community memberships, are used to extract social dimensions. By introducing Latent Dirichlet Allocation (LDA) to model the network generation process, nodes’ connection behaviors with different communities can be extracted accurately, which are applied as latent social dimensions for classification. Experiments on various public datasets reveal that the proposed method can obtain satisfactory classification results in comparison to other state-of-the-art methods on smaller social dimensions. Public Library of Science 2016-04-06 /pmc/articles/PMC4822808/ /pubmed/27049849 http://dx.doi.org/10.1371/journal.pone.0152857 Text en © 2016 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Li, Le Xu, Junyi Xiao, Weidong Ge, Bin Behavior Based Social Dimensions Extraction for Multi-Label Classification |
title | Behavior Based Social Dimensions Extraction for Multi-Label Classification |
title_full | Behavior Based Social Dimensions Extraction for Multi-Label Classification |
title_fullStr | Behavior Based Social Dimensions Extraction for Multi-Label Classification |
title_full_unstemmed | Behavior Based Social Dimensions Extraction for Multi-Label Classification |
title_short | Behavior Based Social Dimensions Extraction for Multi-Label Classification |
title_sort | behavior based social dimensions extraction for multi-label classification |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4822808/ https://www.ncbi.nlm.nih.gov/pubmed/27049849 http://dx.doi.org/10.1371/journal.pone.0152857 |
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