HIGHLIGHTS
- who: Sang-Min Choi et al. from the Department of Computer Science, Gyeongsang National University, Jinju-si, Republic of have published the research: Improving Data Sparsity in Recommender Systems Using Matrix Regeneration with Item Features, in the Journal: Mathematics 2023, 11, 292. of 31/Dec/2022
- what: The authors propose a method to improve the dataset sparsity and increase the accuracy of the prediction results by using item features with user responses. The authors compare the prediction results of the approach and conventional CF using the mean absolute error and root mean square error. Users . . .
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