Most real systems consist of a large number of interacting, multi-typed components, while
most contemporary researches model them as homogeneous information networks, without …

Detecting anomalies in data is a vital task, with numerous high-impact applications in areas
such as security, finance, health care, and law enforcement. While numerous techniques …

Problems involving multiple networks are prevalent in many scientific and other domains. In
particular, network alignment, or the task of identifying corresponding nodes in different …

In this paper, we adopt the representation learning approach to align users across multiple
social networks where the social structures of the users are exploited. In particular, we …

Multiple networks naturally appear in numerous high-impact applications. Network
alignment (ie, finding the node correspondence across different networks) is often the very …

The typical aim of User Identity Linkage (UIL) is to detect when users from across different
social platforms are actually one and the same individual. Existing efforts to address this …

Linking accounts of the same user across datasets--even when personally identifying
information is removed or unavailable--is an important open problem studied in many …

Network alignment is the problem of pairing nodes between two graphs such that the paired
nodes are structurally and semantically similar. A well-known application of network …

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

Users nowadays are normally involved in multiple (usually more than two) online social
networks simultaneously to enjoy more social network services. Some of the networks that …