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Extreme Residual Connected Convolution-Based Collaborative Filtering for Document Context-Aware Rating Prediction.

, , , , and . IEEE Access, (2020)

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Integrating an Attention Mechanism and Convolution Collaborative Filtering for Document Context-Aware Rating Prediction., , , , and . IEEE Access, (2019)A probabilistic model derived term weighting scheme for text classification., , , and . Pattern Recognit. Lett., (2018)Relationship-aware contrastive learning for social recommendations., , , , , and . Inf. Sci., (June 2023)A Novel Recommendation Method Based on User's Interest and Heterogeneous Information., , , , , and . APWeb Workshops, volume 9865 of Lecture Notes in Computer Science, page 90-101. (2016)Reliable Negative Extracting Based on kNN for Learning from Positive and Unlabeled Examples., and . J. Comput., 4 (1): 94-101 (2009)A New Weighted Similarity Method Based on Neighborhood User Contributions for Collaborative Filtering., , , , , , and . DSC, page 376-381. IEEE Computer Society, (2016)A Novel Recommendation Algorithm Based on Heterogeneous Information Network Similarity and Preference Diffusion., , , , , and . WAIM Workshops, volume 9391 of Lecture Notes in Computer Science, page 53-64. Springer, (2015)一种基于Bhattacharyya系数和项目相关性的协同过滤算法 (Collaborative Filtering Algorithm Based on Bhattacharyya Coefficient and Item Correlation)., , , , and . 计算机科学, 44 (12): 52-57 (2017)Learning from Positive and Unlabeled Examples: A Survey., and . ISIP, page 650-654. IEEE Computer Society, (2008)Trust-Aware Collaborative Filtering with a Denoising Autoencoder., , , , and . Neural Processing Letters, 49 (2): 835-849 (2019)