Supervised Collaborative Filtering Based on Ridge Alternating Least Squares and Iterative Projection Pursuit
文献类型：期刊论文
| 作者 | Chen, Bo-Wei2; Ji, Wen3; Rho, Seungmin1; Gu, Yu4 |
| 刊名 | IEEE ACCESS
 |
| 出版日期 | 2017 |
| 卷号 | 5页码:6600-6607 |
| 关键词 | Incomplete data analysis privacy preservation supervised collaborative filtering collaborative filtering (CF) alternating least squares (ALS) supervised data imputation data imputation singular value decomposition (SVD) supervised nonnegative matrix factorization (NMF) recommendation system low-rank matrix approximation matrix completion matrix factorization iterative projection pursuit |
| ISSN号 | 2169-3536 |
| DOI | 10.1109/ACCESS.2017.2688449 |
| 英文摘要 | This paper presents a supervised data imputation based on the class-dependent matrix factors, which are generated during matrix factorization. The proposed ridge alternating least squares imputation uses class information to create substituted values, which approximate the characteristics of their corresponding classes, for missing entries. In the training phase, the incomplete data with label information are divided into different classes based on their labels, such that basis matrices become class-dependent. Subsequently, iterative projection pursuit is proposed to perform imputation for testing data by computing the linear combination of these class-dependent basis matrices and their corresponding reconstruction weights. The class-dependent basis matrix with the minimum loss during reconstruction is regarded as the correct imputation for a testing sample, of which the substituted values are derived from the matrix factors of its class. Experiments on open data sets showed that the proposed method successfully decreased the imputation error by 40.52% on average, better than typical unsupervised collaborative filtering, while maintaining classification accuracy. |
| 资助项目 | National Natural Science Foundation of China[61572466] ; Beijing Natural Science Foundation[4162059] |
| WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
| 语种 | 英语 |
| WOS记录号 | WOS:000401431300131 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/7185]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Ji, Wen; Gu, Yu |
| 作者单位 | 1.Sungkyul Univ, Dept Media Software, Anyang 430742, South Korea 2.Monash Univ, Sch Informat Technol, Melbourne, Vic 3800, Australia 3.Chinese Acad Sci, Beijing Key Lab Mobile Comp & Pervas Device, Inst Comp Technol, Beijing 100190, Peoples R China 4.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Bo-Wei,Ji, Wen,Rho, Seungmin,et al. Supervised Collaborative Filtering Based on Ridge Alternating Least Squares and Iterative Projection Pursuit[J]. IEEE ACCESS,2017,5:6600-6607. |
| APA | Chen, Bo-Wei,Ji, Wen,Rho, Seungmin,&Gu, Yu.(2017).Supervised Collaborative Filtering Based on Ridge Alternating Least Squares and Iterative Projection Pursuit.IEEE ACCESS,5,6600-6607. |
| MLA | Chen, Bo-Wei,et al."Supervised Collaborative Filtering Based on Ridge Alternating Least Squares and Iterative Projection Pursuit".IEEE ACCESS 5(2017):6600-6607. |
入库方式： OAI收割
来源：计算技术研究所
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