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

This work aims to tackle the challenging heterogeneous graph encoding problem in the text-
to-SQL task. Previous methods are typically node-centric and merely utilize different weight …

Online reviews have become an increasingly important resource for decision making and
product designing. But reviews systems are often targeted by opinion spamming. Although …

Heterogeneous information networks usually contain different kinds of nodes and
distinguishing types of relations, which can preserve more information than homogeneous …

A network embedding is a representation of a large graph in a low-dimensional space,
where vertices are modeled as vectors. The objective of a good embedding is to preserve …

Collective classification has attracted considerable attention in the last decade, where the
labels within a group of instances are correlated and should be inferred collectively, instead …

Social networks are heterogeneous systems composed of different types of nodes (eg users,
content, groups, etc.) and relations (eg social or similarity relations). While learning and …

Heterogeneous Information Networks (HINs) comprise nodes of different types inter-
connected through diverse semantic relationships. In many real-world applications, nodes in …

Text classification is an important problem with many applications. Traditional approaches
represent text as a bag-of-words and build classifiers based on this representation. Rather …

Collective classification, as an important technique to study networked data, aims to exploit
the label autocorrelation for a group of inter-connected entities with complex dependencies …