Overseas short video recommendations: A multimodal graph convolutional network approach incorporating cultural preferences
In an age of cultural globalization, short video platforms are springing up around the globe, making it challenging to cater to a diverse mix of users with varied preferences and cultural backgrounds. In our research, we propose a novel suggestion model of short video material for international vide...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | Egyptian Informatics Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S111086652500009X |
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| author | Xishi Liu Haolin Wang Dan Li |
| author_facet | Xishi Liu Haolin Wang Dan Li |
| author_sort | Xishi Liu |
| collection | DOAJ |
| description | In an age of cultural globalization, short video platforms are springing up around the globe, making it challenging to cater to a diverse mix of users with varied preferences and cultural backgrounds. In our research, we propose a novel suggestion model of short video material for international video apps through user preference modelling via hybrid multi-modal GCN (graph convolutional network). Unlike traditional methods that rely on the overall metadata of the short movies only, our approach jointly considers visual, linguistic and audio features of short movies, as well as user interactions, to propose personalized recommendations. Due to the effectiveness of the proposed method on TikTok and MovieLens dataset with a recall of 0.590 and video label classification accuracy more than 94.9%, The approach demonstrates effective use of resources with a maximum CPU utilization of only 44% whilst maintaining high user satisfaction across different age groups. Overall, the results have an implication that the proposed approach can lead to better user interaction and satisfaction in a culturally diverse environment. |
| format | Article |
| id | doaj-art-5a9fedd0b8cb430eae5a25bedaa49d8d |
| institution | Kabale University |
| issn | 1110-8665 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Egyptian Informatics Journal |
| spelling | doaj-art-5a9fedd0b8cb430eae5a25bedaa49d8d2025-02-07T04:47:15ZengElsevierEgyptian Informatics Journal1110-86652025-03-0129100616Overseas short video recommendations: A multimodal graph convolutional network approach incorporating cultural preferencesXishi Liu0Haolin Wang1Dan Li2School of Media Arts and Communication, Nanjing University of the Arts, Nanjing 210013, Jiangsu, China; Photography School, Communication University of China Nanjing, Nanjing 211172, Jiangsu, ChinaPhotography School, Communication University of China Nanjing, Nanjing 211172, Jiangsu, China; Corresponding author.Arts Council office, Jangsu Art Museum, Nanjing 210018, ChinaIn an age of cultural globalization, short video platforms are springing up around the globe, making it challenging to cater to a diverse mix of users with varied preferences and cultural backgrounds. In our research, we propose a novel suggestion model of short video material for international video apps through user preference modelling via hybrid multi-modal GCN (graph convolutional network). Unlike traditional methods that rely on the overall metadata of the short movies only, our approach jointly considers visual, linguistic and audio features of short movies, as well as user interactions, to propose personalized recommendations. Due to the effectiveness of the proposed method on TikTok and MovieLens dataset with a recall of 0.590 and video label classification accuracy more than 94.9%, The approach demonstrates effective use of resources with a maximum CPU utilization of only 44% whilst maintaining high user satisfaction across different age groups. Overall, the results have an implication that the proposed approach can lead to better user interaction and satisfaction in a culturally diverse environment.http://www.sciencedirect.com/science/article/pii/S111086652500009XShort videoCultural exportationPreference perceptionMultimodal graph convolutional networkMaximum pooling |
| spellingShingle | Xishi Liu Haolin Wang Dan Li Overseas short video recommendations: A multimodal graph convolutional network approach incorporating cultural preferences Egyptian Informatics Journal Short video Cultural exportation Preference perception Multimodal graph convolutional network Maximum pooling |
| title | Overseas short video recommendations: A multimodal graph convolutional network approach incorporating cultural preferences |
| title_full | Overseas short video recommendations: A multimodal graph convolutional network approach incorporating cultural preferences |
| title_fullStr | Overseas short video recommendations: A multimodal graph convolutional network approach incorporating cultural preferences |
| title_full_unstemmed | Overseas short video recommendations: A multimodal graph convolutional network approach incorporating cultural preferences |
| title_short | Overseas short video recommendations: A multimodal graph convolutional network approach incorporating cultural preferences |
| title_sort | overseas short video recommendations a multimodal graph convolutional network approach incorporating cultural preferences |
| topic | Short video Cultural exportation Preference perception Multimodal graph convolutional network Maximum pooling |
| url | http://www.sciencedirect.com/science/article/pii/S111086652500009X |
| work_keys_str_mv | AT xishiliu overseasshortvideorecommendationsamultimodalgraphconvolutionalnetworkapproachincorporatingculturalpreferences AT haolinwang overseasshortvideorecommendationsamultimodalgraphconvolutionalnetworkapproachincorporatingculturalpreferences AT danli overseasshortvideorecommendationsamultimodalgraphconvolutionalnetworkapproachincorporatingculturalpreferences |