Deep learning (DL) techniques have been widely used in recommender systems for user
modeling and matching function learning based on historical interaction matrix. However …

Cybersecurity, as a crucial aspect of the information society, requires significant attention.
Fortunately, the concept of trust, originating from the field of sociology, has been under …

In this era of big data, the amount of video content has dramatically increased with an
exponential broadening of video streaming services. Hence, it has become very strenuous …

Due to the expansion of e-business, the availability of products on the internet has massively
increased. Finding suitable stuff from the vast array of products available on the internet is a …

With the advent of the modern era, deep neural networks have dominated recommender
systems, as they can effectively capture complex interactions. Nevertheless, there is still a …

A recommender system (RS) is a data filtering technique that suggests the appropriate
information to the end-user. Collaborative filtering is the most frequently deployed algorithm …

In recent years, collaborative filtering (CF) techniques have become one of the most
popularly used techniques for providing personalized services to users. CF techniques …

In this digital era, users and service providers are facing various decisions that prompt data
over-burden. The choices should be separated and focused on or altered so that the actual …

Expert assessments with pre-defined numerical or language terms can limit the scope of
decision-making models. We propose that decision-making models can incorporate expert …

The tremendous growth in information over the last decade leads to information
overwhelming problems for accessing personalized products. The recommender framework …