Cargando…

A Semantic-Enhancement-Based Social Network User-Alignment Algorithm

User alignment can associate multiple social network accounts of the same user. It has important research implications. However, the same user has various behaviors and friends across different social networks. This will affect the accuracy of user alignment. In this paper, we aim to improve the acc...

Descripción completa

Detalles Bibliográficos
Autores principales: Huang, Yuanhao, Zhao, Pengcheng, Zhang, Qi, Xing, Ling, Wu, Honghai, Ma, Huahong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9858570/
https://www.ncbi.nlm.nih.gov/pubmed/36673313
http://dx.doi.org/10.3390/e25010172
_version_ 1784874134741712896
author Huang, Yuanhao
Zhao, Pengcheng
Zhang, Qi
Xing, Ling
Wu, Honghai
Ma, Huahong
author_facet Huang, Yuanhao
Zhao, Pengcheng
Zhang, Qi
Xing, Ling
Wu, Honghai
Ma, Huahong
author_sort Huang, Yuanhao
collection PubMed
description User alignment can associate multiple social network accounts of the same user. It has important research implications. However, the same user has various behaviors and friends across different social networks. This will affect the accuracy of user alignment. In this paper, we aim to improve the accuracy of user alignment by reducing the semantic gap between the same user in different social networks. Therefore, we propose a semantically enhanced social network user alignment algorithm (SENUA). The algorithm performs user alignment based on user attributes, user-generated contents (UGCs), and user check-ins. The interference of local semantic noise can be reduced by mining the user’s semantic features for these three factors. In addition, we improve the algorithm’s adaptability to noise by multi-view graph-data augmentation. Too much similarity of non-aligned users can have a large negative impact on the user-alignment effect. Therefore, we optimize the embedding vectors based on multi-headed graph attention networks and multi-view contrastive learning. This can enhance the similar semantic features of the aligned users. Experimental results show that SENUA has an average improvement of 6.27% over the baseline method at hit-precision30. This shows that semantic enhancement can effectively improve user alignment.
format Online
Article
Text
id pubmed-9858570
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-98585702023-01-21 A Semantic-Enhancement-Based Social Network User-Alignment Algorithm Huang, Yuanhao Zhao, Pengcheng Zhang, Qi Xing, Ling Wu, Honghai Ma, Huahong Entropy (Basel) Article User alignment can associate multiple social network accounts of the same user. It has important research implications. However, the same user has various behaviors and friends across different social networks. This will affect the accuracy of user alignment. In this paper, we aim to improve the accuracy of user alignment by reducing the semantic gap between the same user in different social networks. Therefore, we propose a semantically enhanced social network user alignment algorithm (SENUA). The algorithm performs user alignment based on user attributes, user-generated contents (UGCs), and user check-ins. The interference of local semantic noise can be reduced by mining the user’s semantic features for these three factors. In addition, we improve the algorithm’s adaptability to noise by multi-view graph-data augmentation. Too much similarity of non-aligned users can have a large negative impact on the user-alignment effect. Therefore, we optimize the embedding vectors based on multi-headed graph attention networks and multi-view contrastive learning. This can enhance the similar semantic features of the aligned users. Experimental results show that SENUA has an average improvement of 6.27% over the baseline method at hit-precision30. This shows that semantic enhancement can effectively improve user alignment. MDPI 2023-01-15 /pmc/articles/PMC9858570/ /pubmed/36673313 http://dx.doi.org/10.3390/e25010172 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Huang, Yuanhao
Zhao, Pengcheng
Zhang, Qi
Xing, Ling
Wu, Honghai
Ma, Huahong
A Semantic-Enhancement-Based Social Network User-Alignment Algorithm
title A Semantic-Enhancement-Based Social Network User-Alignment Algorithm
title_full A Semantic-Enhancement-Based Social Network User-Alignment Algorithm
title_fullStr A Semantic-Enhancement-Based Social Network User-Alignment Algorithm
title_full_unstemmed A Semantic-Enhancement-Based Social Network User-Alignment Algorithm
title_short A Semantic-Enhancement-Based Social Network User-Alignment Algorithm
title_sort semantic-enhancement-based social network user-alignment algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9858570/
https://www.ncbi.nlm.nih.gov/pubmed/36673313
http://dx.doi.org/10.3390/e25010172
work_keys_str_mv AT huangyuanhao asemanticenhancementbasedsocialnetworkuseralignmentalgorithm
AT zhaopengcheng asemanticenhancementbasedsocialnetworkuseralignmentalgorithm
AT zhangqi asemanticenhancementbasedsocialnetworkuseralignmentalgorithm
AT xingling asemanticenhancementbasedsocialnetworkuseralignmentalgorithm
AT wuhonghai asemanticenhancementbasedsocialnetworkuseralignmentalgorithm
AT mahuahong asemanticenhancementbasedsocialnetworkuseralignmentalgorithm
AT huangyuanhao semanticenhancementbasedsocialnetworkuseralignmentalgorithm
AT zhaopengcheng semanticenhancementbasedsocialnetworkuseralignmentalgorithm
AT zhangqi semanticenhancementbasedsocialnetworkuseralignmentalgorithm
AT xingling semanticenhancementbasedsocialnetworkuseralignmentalgorithm
AT wuhonghai semanticenhancementbasedsocialnetworkuseralignmentalgorithm
AT mahuahong semanticenhancementbasedsocialnetworkuseralignmentalgorithm