Cross-domain incremental recommendation system based on meta learning
Author:
Funder
Ministry of Science and Technology, Taiwan
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12652-022-03911-z.pdf
Reference27 articles.
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2. Chang X, Nie F, Wang S, Yang Y, Zhou X, Zhang C (2015) Compound rank-k projections for bilinear analysis. IEEE Trans Neural Netw Learn Syst 27(7):1502–1513
3. Chen T, He T, Benesty M, Khotilovich V, Tang Y, Cho H (2015) Xgboost: extreme gradient boosting. Microsoft Rep 1(4):1–4
4. Chen K, Yao L, Zhang D, Wang X, Chang X, Nie F (2020) A semisupervised recurrent convolutional attention model for human activity recognition. IEEE Trans Neural Netw Learn Syst 31(5):1747–1756. https://doi.org/10.1109/TNNLS.2019.2927224
5. Cheng H-T, Koc L, Harmsen J, Shaked T, Chandra T, Aradhye H, Anderson G, Corrado G, Chai W, Ispir M (2016) Wide and deep learning for recommender systems. In: Proceedings of the 1st workshop on deep learning for recommender systems, pp 7–10
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