Equip** machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

Serverless computing is an emerging cloud computing paradigm, being adopted to develop
a wide range of software applications. It allows developers to focus on the application logic …

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 …

Transforming unstructured text into structured and meaningful forms, organized by useful
category labels, is a fundamental step in text mining for downstream analysis and …

Digital transformation (DT) is prevalent in businesses today. However, current studies to
guide DT are mostly qualitative, resulting in a strong call for quantitative evidence of exactly …

Graph Neural Networks (GNNs) have demonstrated great power in many network analytical
tasks. However, graphs (ie, networks) in the real world are usually text-rich, implying that …

Fringe groups and organizations have a long history of using euphemisms—ordinary-
sounding words with a secret meaning—to conceal what they are discussing. Nowadays …

Automatic construction of a taxonomy supports many applications in e-commerce, web
search, and question answering. Existing taxonomy expansion or completion methods …

Self-supervised representation learning on text-attributed graphs, which aims to create
expressive and generalizable representations for various downstream tasks, has received …

Taxonomies are important knowledge ontologies that underpin numerous applications on a
daily basis, but many taxonomies used in practice suffer from the low coverage issue. We …