Recommender systems, which provide users with recommendations of content suited to
their needs, have received great attention in today's online business world. However, most …

In the era of big data, recommender system (RS) has become an effective information
filtering tool that alleviates information overload for Web users. Collaborative filtering (CF) …

Collaborative filtering (CF), one of the most successful recommendation approaches,
continues to attract interest in both academia and industry. However, one key issue limiting …

Today, people frequently communicate through interactions and exchange knowledge over
the social web in various formats. Social connections have been substantially improved by …

Collaborative filtering (CF) has become one of the most popular and widely used methods in
recommender systems, but its performance degrades sharply for users with rare interaction …

Collaborative Filtering (CF) based recommender systems often suffer from the sparsity
problem, particularly for new and inactive users when they use the system. The emerging …

Recommender systems are used to accurately and actively provide users with potentially
interesting information or services. Collaborative filtering is a widely adopted approach to …

Collaborative Filtering (CF) is the most popular method for recommender systems. The
principal idea of CF is that users might be interested in items that are favorited by similar …

Collaborative filtering (CF) is a widely used approach in recommender systems to solve
many real-world problems. Traditional CF-based methods employ the user-item matrix …

Collaborative Filtering (CF) algorithms have been widely used to provide personalized
recommendations in e-commerce websites and social network applications. Among them …