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 …

Entity Set Expansion (ESE) is a promising task which aims to expand entities of the target
semantic class described by a small seed entity set. Various NLP and IR applications will …

Entity Set Expansion (ESE) is a valuable task that aims to find entities of the target semantic
class described by given seed entities. Various Natural Language Processing (NLP) and …

Traditional event extraction methods require predefined event types and their corresponding
annotations to learn event extractors. These prerequisites are often hard to be satisfied in …

Automated event detection from news corpora is a crucial task towards mining fast-evolving
structured knowledge. As real-world events have different granularities, from the top-level …

With the rapid development of deep learning, training Big Models (BMs) for multiple
downstream tasks becomes a popular paradigm. Researchers have achieved various …

Conventional closed-world information extraction (IE) approaches rely on human ontologies
to define the scope for extraction. As a result, such approaches fall short when applied to …

Synonyms refer to different expressions for the same entity in the text and affect entity-centric
text mining research performance. Therefore, synonym recognition has become a promising …

The model's ability to understand synonymous expression is crucial in many kinds of
downstream tasks. It will make the model to better understand the similarity between context …

Ontologies provide formal representation of knowledge shared within Semantic Web
applications and Ontology learning from text involves the construction of ontologies from a …