Social recommendation leverages social information to alleviate data sparsity and cold-start
issues of collaborative filtering (CF) methods. Most existing works model user interests …

Social recommendation has emerged to leverage social connections among users for
predicting users' unknown preferences, which could alleviate the data sparsity issue in …

Collaborative Filtering (CF) is one of the most successful approaches for recommender
systems. With the emergence of online social networks, social recommendation has become …

Social recommendation leverages social information to solve data sparsity and cold-start
problems in traditional collaborative filtering methods. However, most existing models …

Social relations are leveraged to tackle the sparsity issue of user-item interaction data in
recommendation under the assumption of social homophily. However, social …

Collaborative filtering (CF) is one of the most popular techniques for building recommender
systems. To alleviate the data sparsity issue in CF, social recommendation has emerged by …

Generating recommendations based on user-item interactions and user-user social relations
is a common use case in web-based systems. These connections can be naturally …

In recent years, researchers attempt to utilize online social information to alleviate data
sparsity for collaborative filtering, based on the rationale that social networks offers the …

Collaborative filtering (CF) is one of the most popular techniques for building recommender
systems. To overcome the data sparsity in CF, social recommender systems have emerged …

Social recommendation is effective in improving the recommendation performance by
leveraging social relations from online social networking platforms. Social relations among …