Comparative analysis of collaborative filtering techniques for the multi-criteria recommender systems
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 …
Netflix, etc. to recommend new items to users. Among various recommendation techniques …
A Multi-Criteria Collaborative Filtering Recommender System Using Clustering and Regression Techniques.
M Nilashi, M Dalvi-Esfahani… - Journal of Soft …, 2016 - search.ebscohost.com
Abstract Traditional Collaborative Filtering (CF) recommender systems recommend the
items to users based on their single ratings which are used to match similar users. In multi …
items to users based on their single ratings which are used to match similar users. In multi …
Matrix factorization and regression-based approach for multi-criteria recommender system
Recommender systems (RS) try to solve information overload problem by providing the most
relevant items to users from a large set of items. Collaborative filtering (CF), a popular …
relevant items to users from a large set of items. Collaborative filtering (CF), a popular …
A novel deep multi-criteria collaborative filtering model for recommendation system
Recommender systems have been in existence everywhere with most of them using single
ratings in prediction. However, multi-criteria predictions have been proved to be more …
ratings in prediction. However, multi-criteria predictions have been proved to be more …
A mixed collaborative recommender system using singular value decomposition and item similarity
Nowadays, Recommendation system plays a vital role in industries like e-commerce, music
apps or newsgroup, retailers, etc. Broadly, recommender system techniques are categorized …
apps or newsgroup, retailers, etc. Broadly, recommender system techniques are categorized …
Hybrid recommendation approaches for multi-criteria collaborative filtering
Recommender systems are software tools and techniques for suggesting items in an
automated fashion to users tailored their preferences. Collaborative Filtering (CF) …
automated fashion to users tailored their preferences. Collaborative Filtering (CF) …
An efficient approach for improving the predictive accuracy of multi-criteria recommender system
Recommender Systems are useful information filtering tools that have reduced information
overload over the web. Collaborative filtering (CF) is one of the extensively used …
overload over the web. Collaborative filtering (CF) is one of the extensively used …
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 …
users. They use previous history of the users-items interactions, eg purchase history and/or …
Comprehensive evaluation of matrix factorization models for collaborative filtering recommender systems
J Bobadilla, J Dueñas-Lerín, F Ortega… - arXiv preprint arXiv …, 2024 - arxiv.org
Matrix factorization models are the core of current commercial collaborative filtering
Recommender Systems. This paper tested six representative matrix factorization models …
Recommender Systems. This paper tested six representative matrix factorization models …
Collaborative filtering using non-negative matrix factorisation
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 …
gathers users' ratings and then predicts what users will rate based on their similarity to other …