Ratings of a user to most items in recommender systems are usually missing not at random
(MNAR), largely because users are free to choose which items to rate. To achieve unbiased …

Food recommendation systems play a pivotal role in sha** dietary salubrity and fostering
sustainable lifestyles by recommending recipes and foodstuffs that align with user …

With the explosive growth of users and items, Recommender Systems (RS) are facing
unprecedented challenges on both retrieval efficiency and storage cost. Fortunately …

Recommender systems (RS) help to capture users' personalized interests and are
increasingly important across social media, e-commerce, and various online applications …

Feature modeling, which involves feature representation learning and leveraging, plays an
essential role in industrial recommendation systems. However, the data distribution in real …

Recommendation systems (RS) has become integral to numerous applications, ranging
from e-commerce to content streaming. A critical problem in RS is that the ratings are …

In the information era, recommendation systems play a crucial role in mitigating information
overload by predicting user preferences based on historical interactions. However …

Recommender systems (RS) are increasingly important in social media, entertainment, and
e-commerce in the information explosion era. However, the collected data contains many …