Nowadays, it is common for one natural person to join multiple social networks to enjoy
different kinds of services. Linking identical users across multiple social networks, also …

In this work, we investigate the user identity linkage task across different social media
platforms based on heterogeneous multi-modal posts and social connections. This task is …

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

User identity linkage (UIL) across social networks has recently attracted an increasing
amount of attention due to its significant research challenges and practical value. Most of the …

Recent years have witnessed increasing attention on the application of graph alignment to
on-Web tasks, such as knowledge graph integration and social network linking. Despite …

Abstract Generative Adversarial Network (GAN) has become an active research field due to
its capability to generate quality simulation data. However, two consistent distributions …

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 …

Network alignment, in general, seeks to discover the hidden underlying correspondence
between nodes across two (or more) networks when given their network structure. However …

With the increasing popularity and diversity of social media, users tend to join multiple social
platforms to enjoy different types of services. User identity linkage, which aims to link …

Nowadays, it is common for a person to possess different identities on multiple social
platforms. Social network alignment aims to match the identities that from different networks …