A Dataset for Multimodal Fashion Recommender Model
The result of this study is a DMFRM-202k dataset consisting of 202,189 images with respective metadata and 4,697,573 ratings from 3,117,073 users. It also includes a fine-tuned ResNet50 model and other sub-datasets. The primary scope of this dataset is to support the development of multimodal fashio...
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| 第一著者: | |
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| フォーマット: | Dataset |
| 言語: | 英語 |
| 出版事項: |
Department of Computer Science and Engineering - Obafemi Awolowo University
2023
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| オンライン･アクセス: | https://ir.oauife.edu.ng/handle/123456789/6319 |
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| 要約: | The result of this study is a DMFRM-202k dataset consisting of 202,189 images with respective metadata and 4,697,573 ratings from 3,117,073 users. It also includes a fine-tuned ResNet50 model and other sub-datasets. The primary scope of this dataset is to support the development of multimodal fashion recommendation models. This is probably the first large-scale dataset in the fashion recommendation system community that provides accurately mapped textual and image datasets along with other features such as ratings, image classification, feature vectors, and dataset split into the train, validation, and test sets. The developed dataset is rich and helpful in developing various recommendation models. |
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