Supervised Collaborative Filtering Based on Ridge Alternating Least Squares and Iterative Projection Pursuit

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 c...

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Bibliographic Details
Main Authors: Bo-Wei Chen, Wen Ji, Seungmin Rho, Yu Gu
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/7888956/