Heterogeneous information network (HIN) embedding aims to embed multiple types of
nodes into a low-dimensional space. Although most existing HIN embedding methods …

Existing studies for representation learning of homogeneous information networks cannot be
applicable to academic heterogeneous information networks (HINs) with multi-type nodes …

The current state-of-the-art Entity Detection and Linking (EDL) systems are geared towards
general corpora and cannot be directly applied to the specific domain effectively due to the …

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

With the rapid development and wide application of big data technology, users'
unauthorized access to resources becomes one of the main problems that restrict the secure …

Predicting links in information networks requires deep understanding and careful modeling
of network structure. Network embedding, which aims to learn low-dimensional …

The task of entity linking aims to map the entity reference in the text with the unambiguous
entity in the knowledge base. However, under the background of the continuous growth of …

Nowadays, users are encouraged to activate across multiple online social networks
simultaneously. User identity linkage, which aims to reveal the correspondence among …

In recent years, relationship prediction in heterogeneous information networks (HINs) has
become an active topic. The most essential part of this task is how to effectively represent …

Network embedding has shown its effectiveness in embedding homogeneous networks.
Compared with homogeneous networks, heterogeneous information networks (HINs) …