Object detection and multimodal learning for product recommendations
This study showcases how deep learning can be applied to automated information extraction in fashion data to create a recommendation system. The proposed approach is an algorithm for recommending multiple products based on visual and textual features, ensuring compatibility with query items. The ob...
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| Format: | Article |
| Language: | English |
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Gdańsk University of Technology
2025-01-01
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| Series: | TASK Quarterly |
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| Online Access: | https://journal.mostwiedzy.pl/TASKQuarterly/article/view/3024 |
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| _version_ | 1841553362944786432 |
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| author | Karolina Selwon Paweł Wnuk |
| author_facet | Karolina Selwon Paweł Wnuk |
| author_sort | Karolina Selwon |
| collection | DOAJ |
| description |
This study showcases how deep learning can be applied to automated information extraction in fashion data to create a recommendation system. The proposed approach is an algorithm for recommending multiple products based on visual and textual features, ensuring compatibility with query items. The object detection model can detect many products across different garment categories. The study utilized public e-commerce datasets and trained models using deep learning methods. The compatibility model has shown promising results in automating recommendations of compatible products based on user interests. The study experimented with multiple pre-trained feature extraction models and successfully trained the object detection model for fashion article detection and localization task. Overall, the goal is to deploy the method to enhance its effectiveness and usefulness in providing a satisfying shopping experience for e-commerce users.
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| format | Article |
| id | doaj-art-2fbbc34574f94d77907a4522837ebd3b |
| institution | Kabale University |
| issn | 1428-6394 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Gdańsk University of Technology |
| record_format | Article |
| series | TASK Quarterly |
| spelling | doaj-art-2fbbc34574f94d77907a4522837ebd3b2025-01-09T10:23:56ZengGdańsk University of TechnologyTASK Quarterly1428-63942025-01-01272Object detection and multimodal learning for product recommendationsKarolina SelwonPaweł Wnuk0Shopai sp. z o.o This study showcases how deep learning can be applied to automated information extraction in fashion data to create a recommendation system. The proposed approach is an algorithm for recommending multiple products based on visual and textual features, ensuring compatibility with query items. The object detection model can detect many products across different garment categories. The study utilized public e-commerce datasets and trained models using deep learning methods. The compatibility model has shown promising results in automating recommendations of compatible products based on user interests. The study experimented with multiple pre-trained feature extraction models and successfully trained the object detection model for fashion article detection and localization task. Overall, the goal is to deploy the method to enhance its effectiveness and usefulness in providing a satisfying shopping experience for e-commerce users. https://journal.mostwiedzy.pl/TASKQuarterly/article/view/3024object detectionmultimodal learningfeatures extraction |
| spellingShingle | Karolina Selwon Paweł Wnuk Object detection and multimodal learning for product recommendations TASK Quarterly object detection multimodal learning features extraction |
| title | Object detection and multimodal learning for product recommendations |
| title_full | Object detection and multimodal learning for product recommendations |
| title_fullStr | Object detection and multimodal learning for product recommendations |
| title_full_unstemmed | Object detection and multimodal learning for product recommendations |
| title_short | Object detection and multimodal learning for product recommendations |
| title_sort | object detection and multimodal learning for product recommendations |
| topic | object detection multimodal learning features extraction |
| url | https://journal.mostwiedzy.pl/TASKQuarterly/article/view/3024 |
| work_keys_str_mv | AT karolinaselwon objectdetectionandmultimodallearningforproductrecommendations AT pawełwnuk objectdetectionandmultimodallearningforproductrecommendations |