TECDR: Cross-Domain Recommender System Based on Domain Knowledge Transferor and Latent Preference Extractor
Author:
Affiliation:
1. Key Laboratory of Digital Media, School of Artificial Intelligence and Computer Science, Jiangnan University
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Link
https://www.jstage.jst.go.jp/article/transinf/E107.D/5/E107.D_2023EDP7175/_pdf
Reference32 articles.
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2. [2] T. Wei and J. He, “Comprehensive fair meta-learned recommender system,” Proc. 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp.1989-1999, 2022. 10.1145/3534678.3539269
3. [3] Y. Zheng, S. Liu, Z. Li, and S. Wu, “Cold-start sequential recommendation via meta learner,” Proc. AAAI Conference on Artificial Intelligence, vol.35, no.5, pp.4706-4713, 2021. 10.1609/aaai.v35i5.16601
4. [4] H. Xu, C. Li, Y. Zhang, L. Duan, I.W. Tsang, and J. Shao, “Metacar: Cross-domain meta-augmentation for content-aware recommendation,” IEEE Trans. Knowl. Data Eng., vol.35, no.8, pp.8199-8212, 2023. 10.1109/tkde.2022.3209005
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