Collaborative filtering using non-negative matrix factorisation

MH Aghdam, M Analoui… - Journal of Information …, 2017 - journals.sagepub.com
Collaborative filtering is a popular strategy in recommender systems area. This approach
gathers users' ratings and then predicts what users will rate based on their similarity to other …

[PDF][PDF] A novel non-negative matrix factorization method for recommender systems

MH Aghdam, M Analoui… - Applied Mathematics & …, 2015 - naturalspublishing.com
Recommender systems collect various kinds of data to create their recommendations.
Collaborative filtering is a common technique in this area. This technique gathers and …

Application of nonnegative matrix factorization in recommender systems

MH Aghdam, M Analoui, P Kabiri - 6th International Symposium …, 2012 - ieeexplore.ieee.org
Recommender systems actively collect various kinds of data in order to generate their
recommendations. Collaborative filtering is based on collecting and analyzing information …

Collaborative filtering using orthogonal nonnegative matrix tri-factorization

G Chen, F Wang, C Zhang - Information Processing & Management, 2009 - Elsevier
Collaborative filtering aims at predicting a test user's ratings for new items by integrating
other like-minded users' rating information. The key assumption is that users sharing the …

Comparative analysis of collaborative filtering techniques for the multi-criteria recommender systems

R Singh, P Dwivedi, V Kant - Multimedia Tools and Applications, 2024 - Springer
Recommender systems are essential tools for many e-commerce services, such as Amazon,
Netflix, etc. to recommend new items to users. Among various recommendation techniques …

A survey of collaborative filtering recommender algorithms and their evaluation metrics

M Jalili - International Journal of System Modeling and …, 2017 - zelusinternational.com
Abstract— Recommender systems are often used to provide useful recommendations for
users. They use previous history of the users-items interactions, eg purchase history and/or …

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 …

Contextual collaborative filtering via hierarchical matrix factorization

E Zhong, W Fan, Q Yang - Proceedings of the 2012 SIAM International …, 2012 - SIAM
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 …

[PDF][PDF] Role of matrix factorization model in collaborative filtering algorithm: A survey

D kumar Bokde, S Girase… - CoRR, abs …, 2015 - researchgate.net
ABSTRACT Recommendation Systems apply Information Retrieval techniques to select the
online information relevant to a given user. Collaborative Filtering (CF) is currently most …

A fusion collaborative filtering method for sparse data in recommender systems

C Feng, J Liang, P Song, Z Wang - Information Sciences, 2020 - Elsevier
Collaborative filtering is a fundamental technique in recommender systems, for which
memory-based and matrix-factorization-based collaborative filtering are the two types of …