Probabilistic matrix factorization recommendation approach for integrating multiple information sources
Most previous studies on matrix factorization (MF)-based collaborative filtering (CF) have
focused solely on user rating information for predicting recommendations. However, to …
focused solely on user rating information for predicting recommendations. However, to …
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 …
Boosting response aware model-based collaborative filtering
Recommender systems are promising for providing personalized favorite services.
Collaborative filtering (CF) technologies, making prediction of users' preference based on …
Collaborative filtering (CF) technologies, making prediction of users' preference based on …
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 …
Improving latent factor model based collaborative filtering via integrated folksonomy factors
LUO Xin, Y Ouyang, X ZHANG - International Journal of Uncertainty …, 2011 - World Scientific
Latent Factor Model (LFM) based approaches are becoming popular when implementing
Collaborative Filtering (CF) recommenders, due to their high recommendation accuracy …
Collaborative Filtering (CF) recommenders, due to their high recommendation accuracy …
Improving matrix factorization-based recommender via ensemble methods
X Luo, Y Ouyang, X Zhang - International Journal of Information …, 2011 - World Scientific
One of the most popular approaches to Collaborative Filtering is based on Matrix
Factorization (MF). In this paper, we focus on improving MF-based recommender's accuracy …
Factorization (MF). In this paper, we focus on improving MF-based recommender's accuracy …
Kernelized probabilistic matrix factorization for collaborative filtering: exploiting projected user and item graph
B Pal, M Jenamani - Proceedings of the 12th ACM conference on …, 2018 - dl.acm.org
Matrix Factorization (MF) techniques have already shown its strong foundation in
collaborative filtering (CF), particularly for rating prediction problem. In the basic MF model …
collaborative filtering (CF), particularly for rating prediction problem. In the basic MF model …
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 …
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 …
Sentiment based multi-index integrated scoring method to improve the accuracy of recommender system
To the best of our knowledge, few studies have focused on the inconsistency between user
ratings and reviews as well as natural noise management in recommender systems (RSs) …
ratings and reviews as well as natural noise management in recommender systems (RSs) …