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- W4366959095 abstract "Recommendation systems are widely used in various industries and are seen as one of the effective methods in reducing information overload. This paper selected four common algorithms for implementation and evaluation among many recommendation algorithms. Two traditional collaborative filtering algorithms - User Collaboration Filter and Item-based Collaborative Filtering; most popular algorithms in the recommendation field - Matrix Factorization; and Neural Collaborative Filtering - the algorithm based on Matrix Factorization and combined with neural networks." @default.
- W4366959095 created "2023-04-26" @default.
- W4366959095 creator A5047166842 @default.
- W4366959095 date "2022-09-01" @default.
- W4366959095 modified "2023-10-14" @default.
- W4366959095 title "Implementation and Effectiveness Evaluation of Four Common Algorithms of Recommendation Systems - User Collaboration Filter, Item-based Collaborative Filtering, Matrix Factorization and Neural Collaborative Filtering" @default.
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- W4366959095 doi "https://doi.org/10.1109/cbase57816.2022.00049" @default.
- W4366959095 hasPublicationYear "2022" @default.
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