19 citations · 22 across the 5 of their papers we have counts for
5 papers
Preference Modeling by Exploiting Latent Components of Ratings
Junhua Chen, Wei Zeng, Junming Shao +1
Understanding user preference is essential to the optimization of recommender systems. As a feedback of user's taste, rating scores can directly reflect the preference of a given u…
A Price Driven Hazard Approach to User Retention
Junhua Chen, Wei Zeng, Ge Fan +1
Customer loyalty is crucial for internet services since retaining users of a service to ensure the staying time of the service is of significance for increasing revenue. It demands…
Information filtering in sparse online systems: recommendation via semi-local diffusion
Wei Zeng, An Zeng, Ming-Sheng Shang +1
With the rapid growth of the Internet and overwhelming amount of information and choices that people are confronted with, recommender systems have been developed to effectively sup…
Membership in social networks and the application in information filtering
Wei Zeng, An Zeng, Ming-Sheng Shang +1
During the past a few years, users' membership in the online system (i.e. the social groups that online users joined) are wildly investigated. Most of these works focus on the dete…
Multi-Output Recommender: Items, Groups and Friends, and Their Mutual Contributing Effects
Wei Zeng, Li Chen
Due to the development of social media technology, it becomes easier for users to gather together to form groups. Take the Last.fm for example, users can join groups they may be in…