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Association between community psychological label and user portrait model based on multimodal neural network
By analyzing traditional deep learning multimode retrieval methods, an optimized multimode retrieval model based on convolutional neural network is established. This article proposes an innovative semi-supervised social network user portrait analysis model (UPAM) based on user portrait model, which...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9449543/ https://www.ncbi.nlm.nih.gov/pubmed/36092110 http://dx.doi.org/10.3389/fpsyg.2022.918274 |
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author | Jiang, Hao Yin, Xuehong |
author_facet | Jiang, Hao Yin, Xuehong |
author_sort | Jiang, Hao |
collection | PubMed |
description | By analyzing traditional deep learning multimode retrieval methods, an optimized multimode retrieval model based on convolutional neural network is established. This article proposes an innovative semi-supervised social network user portrait analysis model (UPAM) based on user portrait model, which integrates users’ social information and some known user attribute information (such as educational background and residence) into a unified topic model framework. Finally, a semi-supervised user portrait analysis method based on user social information and partial known user attribute information is proposed. According to the correlation of user attributes, the cross-validation method is used to train model prediction task and improve the prediction effect. In the first-level model, using a different model to extract the features in the user query, the basis of the second hierarchy model, Stacking is used to further integrate characteristics, finally realizing the attribute population forecast, and experimental verification showing the proposed model’s effectiveness in various attributes of a population. |
format | Online Article Text |
id | pubmed-9449543 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94495432022-09-08 Association between community psychological label and user portrait model based on multimodal neural network Jiang, Hao Yin, Xuehong Front Psychol Psychology By analyzing traditional deep learning multimode retrieval methods, an optimized multimode retrieval model based on convolutional neural network is established. This article proposes an innovative semi-supervised social network user portrait analysis model (UPAM) based on user portrait model, which integrates users’ social information and some known user attribute information (such as educational background and residence) into a unified topic model framework. Finally, a semi-supervised user portrait analysis method based on user social information and partial known user attribute information is proposed. According to the correlation of user attributes, the cross-validation method is used to train model prediction task and improve the prediction effect. In the first-level model, using a different model to extract the features in the user query, the basis of the second hierarchy model, Stacking is used to further integrate characteristics, finally realizing the attribute population forecast, and experimental verification showing the proposed model’s effectiveness in various attributes of a population. Frontiers Media S.A. 2022-08-24 /pmc/articles/PMC9449543/ /pubmed/36092110 http://dx.doi.org/10.3389/fpsyg.2022.918274 Text en Copyright © 2022 Jiang and Yin. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Jiang, Hao Yin, Xuehong Association between community psychological label and user portrait model based on multimodal neural network |
title | Association between community psychological label and user portrait model based on multimodal neural network |
title_full | Association between community psychological label and user portrait model based on multimodal neural network |
title_fullStr | Association between community psychological label and user portrait model based on multimodal neural network |
title_full_unstemmed | Association between community psychological label and user portrait model based on multimodal neural network |
title_short | Association between community psychological label and user portrait model based on multimodal neural network |
title_sort | association between community psychological label and user portrait model based on multimodal neural network |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9449543/ https://www.ncbi.nlm.nih.gov/pubmed/36092110 http://dx.doi.org/10.3389/fpsyg.2022.918274 |
work_keys_str_mv | AT jianghao associationbetweencommunitypsychologicallabelanduserportraitmodelbasedonmultimodalneuralnetwork AT yinxuehong associationbetweencommunitypsychologicallabelanduserportraitmodelbasedonmultimodalneuralnetwork |