Social recommendation with learning personal and social latent factors
Due to leveraging social relationships between users as well as their past social behavior,
social recommendation becomes a core component in recommendation systems. Most …
social recommendation becomes a core component in recommendation systems. Most …
Bayesian personalized ranking based on multiple-layer neighborhoods
Recommender systems are widely used on the Internet as tools for data analysis,
processing and discovery. Traditional recommendation algorithms mostly exploit rating …
processing and discovery. Traditional recommendation algorithms mostly exploit rating …
Collaborative filtering-based recommender system: Approaches and research challenges
Due to information explosion, huge number of items are present over web which makes it
difficult for user to find appropriate item from available set of options. Recommender System …
difficult for user to find appropriate item from available set of options. Recommender System …
Collaborative filtering recommendation based on trust and emotion
With the development of personalized recommendations, information overload has been
alleviated. However, the sparsity of the user-item rating matrix and the weak transitivity of …
alleviated. However, the sparsity of the user-item rating matrix and the weak transitivity of …
Movie collaborative filtering with multiplex implicit feedbacks
Movie recommender systems have been widely used in a variety of online networking
platforms to give users reasonable advice from a large number of choices. As a …
platforms to give users reasonable advice from a large number of choices. As a …
Extreme events management using multimedia social networks
Although various researches have demonstrated that Social Networks offer a great
opportunity to detect and manage emergencies and disasters in real life applications, in this …
opportunity to detect and manage emergencies and disasters in real life applications, in this …
Cross‐Border E‐Commerce Personalized Recommendation Based on Fuzzy Association Specifications Combined with Complex Preference Model
D Xiang, Z Zhang - Mathematical Problems in Engineering, 2020 - Wiley Online Library
Since cross‐border e‐commerce involves the export and import of commodities, it is affected
by many policies and regulations, resulting in some special requirements for the …
by many policies and regulations, resulting in some special requirements for the …
TruGRC: Trust-aware group recommendation with virtual coordinators
In recent years, an increase in group activities on websites has led to greater demand for
highly-functional group recommender systems. The goal of group recommendation is to …
highly-functional group recommender systems. The goal of group recommendation is to …
Deep attention user-based collaborative filtering for recommendation
J Chen, X Wang, S Zhao, F Qian, Y Zhang - Neurocomputing, 2020 - Elsevier
The user-based collaborative filtering (UCF) model has been widely used in industry for
recommender systems. UCF predicts a user's interest in an item based on rating information …
recommender systems. UCF predicts a user's interest in an item based on rating information …
Correlated matrix factorization for recommendation with implicit feedback
As a typical latent factor model, Matrix Factorization (MF) has demonstrated its great
effectiveness in recommender systems. Users and items are represented in a shared low …
effectiveness in recommender systems. Users and items are represented in a shared low …