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

Heterogeneous information network (HIN) embedding aims at learning the low-dimensional
representation of nodes while preserving structure and semantics in a HIN. Existing methods …

Heterogenous information network embedding aims to embed heterogenous information
networks (HINs) into low dimensional spaces, in which each vertex is represented as a low …

Learning low-dimensional representations for Heterogeneous Information Networks (HINs)
has drawn increasing attention recently for its effectiveness in real-world applications …

Network embedding in heterogeneous information networks (HINs) is a challenging task,
due to complications of different node types and rich relationships between nodes. As a …

Heterogeneous information network embedding aims to learn low-dimensional node vectors
in heterogeneous information networks (HINs), concerning not only structural information but …

Heterogeneous information networks (HINs) are ubiquitous in real-world applications. In the
meantime, network embedding has emerged as a convenient tool to mine and learn from …

Heterogeneous information network (HIN) embedding has gained increasing interests
recently. However, the current way of random-walk based HIN embedding methods have …

Heterogeneous information network (HIN) embedding, aiming to project HIN into a low-
dimensional space, has attracted considerable research attention. Most of the exiting HIN …

As heterogeneous networks have become increasingly ubiquitous, Heterogeneous
Information Network (HIN) embedding, aiming to project nodes into a low-dimensional …