Multi-linear interactive matrix factorization
Recommender systems, which can significantly help users find their interested items from
the information era, has attracted an increasing attention from both the scientific and …
the information era, has attracted an increasing attention from both the scientific and …
Information filtering via collaborative user clustering modeling
The past few years have witnessed the great success of recommender systems, which can
significantly help users to find out personalized items for them from the information era. One …
significantly help users to find out personalized items for them from the information era. One …
Integrating user-side information into matrix factorization to address data sparsity of collaborative filtering
Recommendation techniques play a vital role in recommending an actual product to an
intended user. The recommendation also supports the user in the decision-making process …
intended user. The recommendation also supports the user in the decision-making process …
Matrix factorization for recommendation with explicit and implicit feedback
S Chen, Y Peng - Knowledge-Based Systems, 2018 - Elsevier
Matrix factorization (MF) methods have proven as efficient and scalable approaches for
collaborative filtering problems. Numerous existing MF methods rely heavily on explicit …
collaborative filtering problems. Numerous existing MF methods rely heavily on explicit …
Pair-wise preference relation based probabilistic matrix factorization for collaborative filtering in recommender system
A Pujahari, DS Sisodia - Knowledge-Based Systems, 2020 - Elsevier
Matrix Factorization (MF) is one of the most popular techniques used in Collaborative
Filtering (CF) based Recommender System (RS). Most of the MF methods tend to remove …
Filtering (CF) based Recommender System (RS). Most of the MF methods tend to remove …
Matrix factorization meets cosine similarity: addressing sparsity problem in collaborative filtering recommender system
H Wen, G Ding, C Liu, J Wang - … and Applications: 16th Asia-Pacific Web …, 2014 - Springer
Matrix factorization (MF) technique has been widely used in collaborative filtering
recommendation systems. However, MF still suffers from data sparsity problem. Although …
recommendation systems. However, MF still suffers from data sparsity problem. Although …
Confidence-aware matrix factorization for recommender systems
Collaborative filtering (CF), particularly matrix factorization (MF) based methods, have been
widely used in recommender systems. The literature has reported that matrix factorization …
widely used in recommender systems. The literature has reported that matrix factorization …
An imputation-based matrix factorization method for improving accuracy of collaborative filtering systems
Matrix-Factorization (MF) is an accurate and scalable approach for collaborative filtering
(CF)-based recommender systems. The performance of matrix MF methods depends on how …
(CF)-based recommender systems. The performance of matrix MF methods depends on how …
List-wise probabilistic matrix factorization for recommendation
J Liu, C Wu, Y Xiong, W Liu - Information Sciences, 2014 - Elsevier
Matrix factorization based recommendation methods gain great success due to their
efficiency and accuracy. But optimizing the objective function in conventional matrix …
efficiency and accuracy. But optimizing the objective function in conventional matrix …
Contextual collaborative filtering via hierarchical matrix factorization
Matrix factorization (MF) has been demonstrated to be one of the most competitive
techniques for collaborative filtering. However, state-of-the-art MFs do not consider …
techniques for collaborative filtering. However, state-of-the-art MFs do not consider …