Fusing fine-grained information of sequential news for personalized news recommendation
In this paper, we propose a novel method that fuses Fine-grained Information of Sequential News for personalized news recommendation (FISN). FISN comprises three primary modules: news encoder, clicked news optimizer and user encoder. The news encoder uses fine-grained information to learn accurate n...
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| 主要な著者: | , , , , |
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| フォーマット: | Conference or Workshop Item |
| 出版事項: |
2023
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| 主題: | |
| オンライン･アクセス: | http://eprints.utm.my/108154/ http://dx.doi.org/10.1007/978-3-031-39821-6_9 |
| タグ: |
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