Recommendation system (RS) is designed to provide personalized services based on the
users' historical data. It has been applied in various fields and is expected to recommend the …

Pointwise prediction and Learning to Rank (L2R) are two hot strategies to model user
preference in recommender systems. Currently, these two types of approaches are often …

With the development of mobile Internet, mobile service is emerging one after another, and
the problem of information overload is becoming ever more serious. As an important tool to …

With the rapid development of internet technology, the number of services with the same or
similar functions on the internet has increased explosively. How to provide users with more …

With the advances in smartphones users install abundant apps to facilitate their daily lives.
Both users and related developers have increasing requirements to understand the mobile …

With the rise of the mobile Internet, the number of mobile applications (apps) has shown
explosive growth, which directly leads to the apps data overload. Currently, the …

Pointwise prediction and Learning to Rank (L2R) are both widely used in recommender
systems. Currently, these two types of approaches are often considered independently, and …

Cross-domain recommendation can alleviate data sparsity problems by leveraging data
from multiple domains. Hence it is becoming an emerging research topic. Existing …

Pointwise prediction and Learning to Rank (L2R) are both widely used in recommender
systems. Currently, these two types of approaches are often considered independently, and …