Interactive recommendation of social network communication between cities based on GNN and user preferences
To further enhance the effectiveness of interactive recommendation for intercity social network communication, the study proposes a novel interactive recommendation model for intercity social network communication. This model focuses on point-of-interest preference migration and recommendation model...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2025-04-01
|
| Series: | Nonlinear Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/nleng-2024-0068 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850199747555491840 |
|---|---|
| author | Gao Yanbo Zhang Lin |
| author_facet | Gao Yanbo Zhang Lin |
| author_sort | Gao Yanbo |
| collection | DOAJ |
| description | To further enhance the effectiveness of interactive recommendation for intercity social network communication, the study proposes a novel interactive recommendation model for intercity social network communication. This model focuses on point-of-interest preference migration and recommendation modeling by integrating the self-attention mechanism, cross-attention mechanism, and graph neural network. The method effectively solves the problem of cross-city users’ interest point preference change and constructs a recommendation framework based on interest point heat. The experimental results showed that the recommendation accuracy of the new model was up to 93.52%. Compared with the existing more advanced recommendation methods, the recommendation coverage of Chengdu–Chongqing dining and food points of interest could be up to 96.72%. The recommendation coverage of Shanghai–Beijing business and residential and science, education, and culture points of interest could be up to 95.17%, and the maximum time reduction was 2.07 s. The contribution of this study is the introduction of a novel graph attention mechanism, which improves the accuracy and stability of recommendations. This provides an effective technical solution for intercity social network communication recommendations. |
| format | Article |
| id | doaj-art-8a2559e29de54849bd852fb2256785e3 |
| institution | OA Journals |
| issn | 2192-8029 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Nonlinear Engineering |
| spelling | doaj-art-8a2559e29de54849bd852fb2256785e32025-08-20T02:12:33ZengDe GruyterNonlinear Engineering2192-80292025-04-01141100293610.1515/nleng-2024-0068Interactive recommendation of social network communication between cities based on GNN and user preferencesGao Yanbo0Zhang Lin1School of Literature and Media, Suzhou University, Suzhou, 234000, ChinaSchool of Literature and Media, Suzhou University, Suzhou, 234000, ChinaTo further enhance the effectiveness of interactive recommendation for intercity social network communication, the study proposes a novel interactive recommendation model for intercity social network communication. This model focuses on point-of-interest preference migration and recommendation modeling by integrating the self-attention mechanism, cross-attention mechanism, and graph neural network. The method effectively solves the problem of cross-city users’ interest point preference change and constructs a recommendation framework based on interest point heat. The experimental results showed that the recommendation accuracy of the new model was up to 93.52%. Compared with the existing more advanced recommendation methods, the recommendation coverage of Chengdu–Chongqing dining and food points of interest could be up to 96.72%. The recommendation coverage of Shanghai–Beijing business and residential and science, education, and culture points of interest could be up to 95.17%, and the maximum time reduction was 2.07 s. The contribution of this study is the introduction of a novel graph attention mechanism, which improves the accuracy and stability of recommendations. This provides an effective technical solution for intercity social network communication recommendations.https://doi.org/10.1515/nleng-2024-0068points of interestuser preferencesocial networksgatcasa |
| spellingShingle | Gao Yanbo Zhang Lin Interactive recommendation of social network communication between cities based on GNN and user preferences Nonlinear Engineering points of interest user preference social networks gat ca sa |
| title | Interactive recommendation of social network communication between cities based on GNN and user preferences |
| title_full | Interactive recommendation of social network communication between cities based on GNN and user preferences |
| title_fullStr | Interactive recommendation of social network communication between cities based on GNN and user preferences |
| title_full_unstemmed | Interactive recommendation of social network communication between cities based on GNN and user preferences |
| title_short | Interactive recommendation of social network communication between cities based on GNN and user preferences |
| title_sort | interactive recommendation of social network communication between cities based on gnn and user preferences |
| topic | points of interest user preference social networks gat ca sa |
| url | https://doi.org/10.1515/nleng-2024-0068 |
| work_keys_str_mv | AT gaoyanbo interactiverecommendationofsocialnetworkcommunicationbetweencitiesbasedongnnanduserpreferences AT zhanglin interactiverecommendationofsocialnetworkcommunicationbetweencitiesbasedongnnanduserpreferences |