With the fast development of online E-commerce Websites and mobile applications, users'
auxiliary information as well as products' textual information can be easily collected to form a …

The growth of data in recent years has motivated the emergence of deep learning in many
Computer Sciences related fields including Recommender System (RS). Deep learning has …

Traditional recommendation techniques present various methods to measure similarity of
users and items to characterize the preferences. However, different similarity measure focus …

Feature selection plays an impactful role in deep recommender systems, which selects a
subset of the most predictive features, so as to boost the recommendation performance and …

Recommender system has recently attracted a lot of attention in the information service
community. Currently, most recommendation models use deep neural networks to learn user …

Due to the great success, deep learning gains much attentions in the research field of
recommendation. In this paper, we review the deep learning based recommendation …

Deep learning based recommender systems have been extensively explored in recent
years. However, the large number of models proposed each year poses a big challenge for …

For many years user textual reviews have been exploited to model user/item representations
for enhancing the performance of the Recommender System (RS). However, the traditional …

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 …

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