An integration method for optimizing the use of explicit and implicit feedback in recommender systems-Reference-Cited by-同舟云学术

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An integration method for optimizing the use of explicit and implicit feedback in recommender systems

Published:2023-10-13 Issue:12 Volume:14 Page:16995-17008
ISSN:1868-5137
Container-title:Journal of Ambient Intelligence and Humanized Computing
language:en
Short-container-title:J Ambient Intell Human Comput

Author:

Lee SeungJoo,Lee Euijong,Seo Young-Duk^ORCID

Funder

Ministry of Science and ICT, South Korea

Publisher

Springer Science and Business Media LLC

Subject

General Computer Science

Link

https://link.springer.com/content/pdf/10.1007/s12652-023-04714-6.pdf

Reference41 articles.

1. Aljunid MF, Huchaiah MD (2022) Integratecf: integrating explicit and implicit feedback based on deep learning collaborative filtering algorithm. Expert Syst Appl 207:117933

2. Bahrani P, Minaei-Bidgoli B, Parvin H, Mirzarezaee M, Keshavarz A (2023) A hybrid semantic recommender system enriched with an imputation method. Multimed Tools Appl. p 1–34

3. Bhuvaneshwari P, Rao AN, Robinson YH (2023) Top-n recommendation system using explicit feedback and outer product based residual cnn. Wirel Pers Commun 128(2):967–983

4. Breese JS, Heckerman D, Kadie C (2013) Empirical analysis of predictive algorithms for collaborative filtering. arXiv:1301.7363

5. Chen C, Ma W, Zhang M, Wang C, Liu Y, Ma S (2023) Revisiting negative sampling vs. non-sampling in implicit recommendation. ACM Trans Inf Syst 41(1):1–25

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