FeatureMF: an item feature enriched matrix factorization model for item recommendation
Matrix Factorization (MF) is one of the most successful Collaborative Filtering (CF)
techniques used in recommender systems due to its effectiveness and ability to deal with …
techniques used in recommender systems due to its effectiveness and ability to deal with …
Attributes coupling based matrix factorization for item recommendation
Recommender systems have attracted lots of attention since they alleviate the information
overload problem for users. Matrix factorization is one of the most widely employed …
overload problem for users. Matrix factorization is one of the most widely employed …
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 …
Leveraging tagging for neighborhood-aware probabilistic matrix factorization
Collaborative Filtering (CF) is a popular way to build recommender systems and has been
successfully employed in many applications. Generally, two kinds of approaches to CF, the …
successfully employed in many applications. Generally, two kinds of approaches to CF, the …
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 …
Ordinal consistency based matrix factorization model for exploiting side information in collaborative filtering
A Pujahari, DS Sisodia - Information Sciences, 2023 - Elsevier
In designing modern recommender systems, item feature information (or side information) is
often ignored as most models focus on exploiting rating information. However, the side …
often ignored as most models focus on exploiting rating information. However, the side …
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 …
Matrix factorization with rating completion: An enhanced SVD model for collaborative filtering recommender systems
Collaborative filtering algorithms, such as matrix factorization techniques, are recently
gaining momentum due to their promising performance on recommender systems. However …
gaining momentum due to their promising performance on recommender systems. However …
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 …
Exploiting implicit item relationships for recommender systems
Collaborative filtering inherently suffers from the data sparsity and cold start problems.
Social networks have been shown useful to help alleviate these issues. However, social …
Social networks have been shown useful to help alleviate these issues. However, social …