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n | "author": "Fuchang Gao", | n | "author": "Adamya Shyama", |
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n | "defined_in": "https://doi.org/10.48550/arXiv.2301.06633", | n | "defined_in": "https://doi.org/10.48550/arXiv.2308.04247", |
| "doi": "10.57702/gijd0y59", | | "doi": "10.57702/gijd0y59", |
| "doi_date_published": "2024-12-02", | | "doi_date_published": "2024-12-02", |
| "doi_publisher": "TIB", | | "doi_publisher": "TIB", |
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n | | n | "extra_authors": [ |
| | | { |
| | | "extra_author": "Vikas Kumara", |
| | | "orcid": "" |
| | | }, |
| | | { |
| | | "extra_author": "Venkateswara Rao Kagitab", |
| | | "orcid": "" |
| | | }, |
| | | { |
| | | "extra_author": "Arun K Pujaric", |
| | | "orcid": "" |
| | | } |
| | | ], |
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| "title": "Recommender Systems" | | "title": "Recommender Systems" |
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| "https://www.cs.ucla.edu/~fuchanggao/papers/Ae2I.pdf", | | |
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n | "notes": "The Movielens 100K and Movielens 1M datasets are used to | n | "notes": "The dataset used in this paper is MovieLens 100K and |
| test the e\ufb00ectiveness of the double autoencoder model.", | | MovieLens 1M.", |
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t | "title": "Movielens 100K and Movielens 1M", | t | "title": "MovieLens 100K and MovieLens 1M", |
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