Recommender systems are effective tools of information filtering that are prevalent due to
increasing access to the Internet, personalization trends, and changing habits of computer …

With the growing volume of online information, recommender systems have been an
effective strategy to overcome information overload. The utility of recommender systems …

The advancement in technology accelerated and opened availability of various alternatives
to make a choice in every domain. In the era of big data it is a tedious and time consuming …

In recent years, deep learning's revolutionary advances in speech recognition, image
analysis, and natural language processing have gained significant attention. Deep learning …

With the recent development of online transactions, recommender systems have
increasingly attracted attention in various domains. The recommender system supports the …

While the recent emergence of a large number of online course resources has made life
more convenient for many people, it has also caused information overload. According to a …

Recommender systems play a significant role in information filtering and have been utilized
in different scenarios, such as e-commerce and social media. With the prosperity of deep …

For the past few years most published research on recommendation algorithms has been
based on deep learning (DL) methods. Following common research practices in our field …

These days, many recommender systems (RS) are utilized for solving information overload
problem in areas such as e-commerce, entertainment, and social media. Although classical …

Recommender systems are efficient tools for filtering online information, which is
widespread owing to the changing habits of computer users, personalization trends, and …