A hybrid recommender system for Gaussian mixture model and enhanced social matrix factorization technology based on multiple interests
R Chen, Q Hua, Q Gao, Y Xing - Mathematical Problems in …, 2018 - Wiley Online Library
Recommender systems are recently becoming more significant in the age of rapid
development of the information technology and pervasive computing to provide e …
development of the information technology and pervasive computing to provide e …
Collaborative filtering based on Gaussian mixture model and improved Jaccard similarity
H Yan, Y Tang - IEEE Access, 2019 - ieeexplore.ieee.org
The recommender systems play an important role in our lives, since it can quickly help users
find what they are interested in. Collaborative filtering has become one of the most widely …
find what they are interested in. Collaborative filtering has become one of the most widely …
Pre-filling collaborative filtering algorithm based on matrix factorization
Nowadays personalized recommendation algorithm of e-commerce can hardly meet the
needs of users as an ever-increasing number of users and items in personalized …
needs of users as an ever-increasing number of users and items in personalized …
A multi-attribute probabilistic matrix factorization model for personalized recommendation
F Tan, L Li, Z Zhang, Y Guo - Pattern Analysis and Applications, 2016 - Springer
Recommendation systems can interpret personal preferences and recommend the most
relevant choices to the benefit of countless users. Attempts to improve the performance of …
relevant choices to the benefit of countless users. Attempts to improve the performance of …
An enhanced social matrix factorization model for recommendation based on social networks using social interaction factors
R Chen, YS Chang, Q Hua, Q Gao, X Ji… - Multimedia Tools and …, 2020 - Springer
Recommender systems are recently becoming more significant in the age of rapid
development of Internet technology and pervasive computing due to their ability in making …
development of Internet technology and pervasive computing due to their ability in making …
An effective preprocessing algorithm for model building in collaborative filtering-based recommender system
T Srikanth, M Shashi - International Journal of Business …, 2019 - inderscienceonline.com
Recommender systems suggest interesting items for online users based on the ratings
expressed by them for the other items maintained globally as the rating matrix. The rating …
expressed by them for the other items maintained globally as the rating matrix. The rating …
A hybrid recommendation approach using LDA and probabilistic matrix factorization
Y Cao, W Li, D Zheng - Cluster Computing, 2019 - Springer
Recommender systems provide users with suggestions and selections. Hybrid approaches
which combine the neighborhood-based methods and the model-based methods have …
which combine the neighborhood-based methods and the model-based methods have …
Preference relation based matrix factorization for recommender systems
Users in recommender systems often express their opinions about different items by rating
the items on a fixed rating scale. The rating information provided by the users is used by the …
the items on a fixed rating scale. The rating information provided by the users is used by the …
CGMF: coupled group-based matrix factorization for recommender system
With the advent of social influence, social recommender systems have become an active
research topic for making recommendations based on the ratings of the users that have …
research topic for making recommendations based on the ratings of the users that have …
A robust multi-criteria recommendation approach with preference-based similarity and support vector machine
J Fan, L Xu - Advances in Neural Networks–ISNN 2013: 10th …, 2013 - Springer
In the next generation of recommender systems, multi-criteria recommendation could be
regarded as one of the most important branches. Compared with traditional recommender …
regarded as one of the most important branches. Compared with traditional recommender …