Collaborative filtering with social local models
Matrix Factorization (MF) is a very popular method for recommendation systems. It assumes
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
Collaborative Filtering with Social Local Models
H Zhao, Q Yao, JTY Kwok, DL Lee - … -IEEE International Conference …, 2017 - repository.ust.hk
Matrix Factorization (MF) is a very popular method for recommendation systems. It assumes
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
Collaborative Filtering with Social Local Models
H Zhao, Q Yao, JT Kwok, D Lun Lee - arXiv e-prints, 2017 - ui.adsabs.harvard.edu
Matrix Factorization (MF) is a very popular method for recommendation systems. It assumes
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
[PDF][PDF] Collaborative Filtering with Social Local Models
H Zhao, Q Yao, JT Kwok, DL Lee - cse.ust.hk
Matrix Factorization (MF) is a very popular method for recommendation systems. It assumes
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
Collaborative Filtering with Social Local Models
H Zhao, Q Yao, JT Kwok, DL Lee - arXiv preprint arXiv:1704.05735, 2017 - arxiv.org
Matrix Factorization (MF) is a very popular method for recommendation systems. It assumes
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
[PDF][PDF] Collaborative Filtering with Social Local Models
H Zhao, Q Yao, JT Kwok, DL Lee - cse.hkust.edu.hk
Matrix Factorization (MF) is a very popular method for recommendation systems. It assumes
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
Collaborative Filtering with Social Local Models
H Zhao - pdfs.semanticscholar.org
• Identify social groups from the social graph and then construct submatrices based on the
groups.• Apply MF to all the submatrices, independently, and obtain multiple groups of user …
groups.• Apply MF to all the submatrices, independently, and obtain multiple groups of user …
[PDF][PDF] Collaborative Filtering with Social Local Models
H Zhao, Q Yao, JT Kwok, DL Lee - cse.ust.hk
Matrix Factorization (MF) is a very popular method for recommendation systems. It assumes
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
[PDF][PDF] Collaborative Filtering with Social Local Models
H Zhao, Q Yao, JT Kwok, DL Lee - hzhaoaf.github.io
Matrix Factorization (MF) is a very popular method for recommendation systems. It assumes
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
[PDF][PDF] Collaborative Filtering with Social Local Models
H Zhao, Q Yao, JT Kwok, DL Lee - researchgate.net
Matrix Factorization (MF) is a very popular method for recommendation systems. It assumes
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …
that the underneath rating matrix is low-rank. However, this assumption can be too restrictive …