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

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 …

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 …

How much has a network changed since yesterday? How different is the wiring of Bob's
brain (a left-handed male) and Alice's brain (a right-handed female), and how is it different …

People nowadays usually participate in multiple online social networks simultaneously to
enjoy more social network services. Besides the common users, social networks providing …

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 …

We propose a two-stage clustering method based on a graph Alignment technique, and a
spectral clustering approach with Multiple Kernel Learning, namely AMKL. Our method is …

Networks have been used to model a variety of real-world phenomena in many domains.
Due to limitations of techniques for data collection, traditional network research has typically …

In this day and age individuals make utilization of various online networking stages for
various purposes. Social identity linkage crosswise over various online networking stages is …