Heterogeneous graphs (HGs) also known as heterogeneous information networks have
become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn …

Link prediction methods anticipate the likelihood of a future connection between two nodes
in a given network. The methods are essential in social networks to infer social interactions …

Due to the flexibility in modelling data heterogeneity, heterogeneous information network
(HIN) has been adopted to characterize complex and heterogeneous auxiliary data in …

Since real-world objects and their interactions are often multi-modal and multi-typed,
heterogeneous networks have been widely used as a more powerful, realistic, and generic …

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

Heterogeneous Information Network (HIN) is a natural and general representation of data in
modern large commercial recommender systems which involve heterogeneous types of …

Recently heterogeneous information network (HIN) analysis has attracted a lot of attention,
and many data mining tasks have been exploited on HIN. As an important data mining task …

Recently, recommender systems play a pivotal role in alleviating the problem of information
overload. Latent factor models have been widely used for recommendation. Most existing …

Deciphering the gene disease association is an important goal in biomedical research. In
this paper, we use a novel relevance measure, called HeteSim, to prioritize candidate …

Social networks, such as Twitter, form a heterogeneous information network (HIN) where
nodes represent domain entities (eg, user, content, advertiser, etc.) and edges represent …