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Most conventional recommendation methods (e.g., matrix factorization) represent user profiles as high-dimensional vectors.
The Tag Genome: Encoding Community Knowledge to Support Novel Interaction
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Earlier work this paper cites.
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Earlier work this paper cites.
Revisiting the Tag Relevance Prediction Problem. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’21) . Association for Computing Machinery, New York, NY, USA, 1768–1772
Denis Kotkov, Alexandr Maslov, and Mats Neovius. 2021 · 2021
Earlier work this paper cites.
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Zheng Chen. 2023 · 2023
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Is ChatGPT a Good Recommender? A Preliminary Study
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Llama 2: Open Foundation and Fine-Tuned Chat Models
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Hanjia Lyu, Song Jiang, Hanqing Zeng, Yinglong Xia, and Jiebo Luo. 2023 · 2023
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CTRL: Connect Collaborative and Language Model for CTR Prediction
Xiangyang Li, Bo Chen, Lu Hou, and Ruiming Tang. 2023a
Cited in the paper.
Yunjia Xi, Weiwen Liu, Jianghao Lin, Xiaoling Cai, Hong Zhu, Jieming Zhu, Bo Chen, Ruiming Tang, Weinan Zhang, Rui Zhang, and Yong Yu. 2023 · 2023
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OpenP5: Benchmarking Foundation Models for Recommendation
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