Knowledge graphs (KGs) have become popular structures for unifying real-world entities by
modelling the relationships between them and their attributes. To support multilingual …

Network alignment plays an important role in a variety of applications. Many traditional
methods explicitly or implicitly assume the alignment consistency which might suffer from …

Knowledge graph (eg Freebase, YAGO) is a multi-relational graph representing rich factual
information among entities of various types. Entity alignment is the key step towards …

Despite achieving remarkable performance, deep graph learning models, such as node
classification and network embedding, suffer from harassment caused by small adversarial …

Graph alignment, which aims at identifying corresponding entities across multiple networks,
has been widely applied in various domains. As the graphs to be aligned are usually …

Recently, the problem of user identification across multiple social networks (UIAMSNs) has
attracted considerable attention since it is a prerequisite for many downstream tasks and …

The user identity linkage that establishes correspondence between users across networks is
a fundamental issue in various social network applications. Efforts have recently been …

The primary concern of numerous online social media network (SMN) platforms is how to
provide users with effective and personalized web services. To achieve this goal, SMN …

Network alignment finds node correspondences across multiple networks, where the
alignment accuracy is of crucial importance because of its profound impact on downstream …

Network alignment, which aims at learning a matching between the same entities across
multiple information networks, often suffers challenges from feature inconsistency, high …