In recent years, different types of review systems have been developed with the
recommender system (RS). RSs are developed based on user textual reviews, ratings, and …

In the era of online business, many e-commerce sites have evolved which recommend items
according to one's needs and interests. Plenty of data is available to be processed to make …

Finding the most influential people is an NP-hard problem that has attracted many
researchers in the field of social networks. The problem is also known as influence …

Collaborative filtering recommender systems (CFRSs) are the key components of successful
E-commerce systems. However, CFRSs are highly vulnerable to “shilling” attacks or “profile …

Recommendation systems (RS) are crucial for alleviating the information overload problem.
Due to its pivotal role in guiding users to make decisions, unscrupulous parties are lured to …

Online rating system plays a crucial role in collaborative filtering recommender systems
(CFRSs). However, CFRSs are highly vulnerable to “shilling” attacks in reality. How to …

One of the important issues concerning the spreading process in social networks is the
influence maximization. This is the problem of identifying the set of the most influential nodes …

Reliability of a recommender system is extremely substantial for the continuity of the system.
Malicious users may harm the reliability of predictions by injecting fake profiles called …

Online rating systems play an important role in recommender systems. Collaborative filtering
recommender systems are highly vulnerable to “shilling” attacks in reality. Although attack …

Collaborative filtering (CF) recommender systems have been shown to be vulnerable to
shilling attacks. How to quickly and effectively detect shilling attacks is a key challenge for …