Purpose This study explores privacy challenges in recommender systems (RSs) and how
they have leveraged privacy-preserving technology for risk mitigation. The study also …

Feature selection is a real-world problem that finds a minimal feature subset from an original
feature set. A good feature selection method, in addition to selecting the most relevant …

Evolutionary multiobjective feature selection (FS) has gained increasing attention in recent
years. However, it still faces some challenges, for example, the frequently appeared …

Mountainous amounts of information are now available in hospitals, finance, counter-
terrorism, education and many other sectors. Those information can offer a rich source for …

As a reliable and valid tool for analyzing uncertain information, fuzzy rough set theory has
attracted widespread concern in feature selection. However, the performance of fuzzy rough …

Imbalanced datasets greatly affect the analysis capability of intrusion detection models,
biasing their classification results toward normal behavior and leading to high false‐positive …

Due to the widespread use of the internet, computer network systems may be exposed to
different types of attacks. For this reason, the intrusion detection systems (IDSs) are often …

In many real-world problems, each sample has more than one label, which may also exist
semantic correlations among labels. However, in multi-label datasets, there are many …

Online social networking applications and their services have become an essential part of
the human lifestyle. These social services help online users in different ways, such as …

With the explosive growth of information on the web and the quick provision of novel web
services, recommendation systems have emerged as efficient mechanism for providing …