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 …

Collaborative filtering is one of the most widely used recommendation system approaches.
One issue in collaborative filtering is how to use a similarity algorithm to increase the …

One of the most prevalent recommendation systems is ranking-oriented collaborative
filtering which employs ranking aggregation. The collaborative filtering study recently …

One of the well-known recommendation systems is memory-based collaborative filtering that
utilizes similarity metrics. Recently, the similarity metrics have taken into account the user …

Trust and reputation systems are one of the most important tools for decision making which
are able to predict the reliability of an agent, taking into account the past experience and …

Graph-based recommender systems (GRSs) analyze the structural information available in
the graphical representation of data to make better recommendations, especially when …

Expert recommendation systems recommend specialized experts in a particular field to
users based on the knowledge of those experts. However, these systems are limited by the …

At E-Commerce stores such as Amazon, eBay, and Taobao, the shopping items and the
query words that customers use to search for the items form a bipartite graph that captures …

The pre‐trained language model (PLM) based on the Transformer encoder, namely BERT,
has achieved state‐of‐the‐art results in the field of Information Retrieval. Existing BERT …

The tourism industry's recommendation system opens the way for capitalising on visitor
demand based on a prior traveller's positive or negative experience at a particular target …