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 …

Relational facts are an important component of human knowledge, which are hidden in vast
amounts of text. In order to extract these facts from text, people have been working on …

Unlike traditional unsupervised clustering, semi-supervised clustering allows users to
provide meaningful structure to the data, which helps the clustering algorithm to match the …

Large language models (LLMs) have great potential for synthetic data generation. This work
shows that useful data can be synthetically generated even for tasks that cannot be solved …

Instant analysis of cybersecurity reports is a fundamental challenge for security experts as
an immeasurable amount of cyber information is generated on a daily basis, which …

We study relation extraction for knowledge base (KB) enrichment. Specifically, we aim to
extract entities and their relationships from sentences in the form of triples and map the …

Link prediction insimple graphs is a fundamental problem in which new links between
vertices are predicted based on the observed structure of the graph. However, in many real …

Given a knowledge base (KB), rule mining finds rules such as “If two people are married,
then they live (most likely) in the same place”. Due to the exponential search space, rule …

Structured and grounded representation of text is typically formalized by closed information
extraction, the problem of extracting an exhaustive set of (subject, relation, object) triplets …

AMiner 1 is a free online academic search and mining system, having collected more than
130,000,000 researcher profiles and over 200,000,000 papers from multiple publication …