Multi-criteria collaborative filtering with high accuracy using higher order singular value decomposition and Neuro-Fuzzy system
Collaborative Filtering (CF) is the most widely used prediction technique in recommender
systems. It makes recommendations based on ratings that users have assigned to items …
systems. It makes recommendations based on ratings that users have assigned to items …
A multi-criteria recommendation system using dimensionality reduction and Neuro-Fuzzy techniques
Multi-criteria collaborative filtering (MC-CF) presents a possibility to provide accurate
recommendations by considering the user preferences in multiple aspects of items …
recommendations by considering the user preferences in multiple aspects of items …
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) …
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 …
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 …
Enhanced multi-criteria recommender system based on fuzzy Bayesian approach
In the area of recommender systems, collaborative filtering is widely used technique for
recommending appropriate items to a user based on the available ratings given by similar …
recommending appropriate items to a user based on the available ratings given by similar …
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 …
Combining user-based and item-based collaborative filtering using machine learning
Collaborative filtering (CF) is typically used for recommending those items to a user which
other like-minded users preferred in the past. User-based collaborative filtering (UbCF) and …
other like-minded users preferred in the past. User-based collaborative filtering (UbCF) and …
A multi-criteria collaborative filtering recommender system for the tourism domain using Expectation Maximization (EM) and PCA–ANFIS
In order to improve the tourist experience, recommender systems are used to offer
personalized information for online users. The hotel industry is a leading stakeholder in the …
personalized information for online users. The hotel industry is a leading stakeholder in the …
[PDF][PDF] An item-based multi-criteria collaborative filtering algorithm for personalized recommender systems
Q Shambour, S Fraihat - International Journal of Advanced …, 2016 - researchgate.net
Recommender Systems are used to mitigate the information overload problem in different
domains by providing personalized recommendations for particular users based on their …
domains by providing personalized recommendations for particular users based on their …