Event Detection (ED) aims to identify event trigger words from a given text and classify it into
an event type. Most of current methods to ED rely heavily on training instances, and almost …

In line with the general trend in artificial intelligence research to create intelligent systems
that combine learning and symbolic techniques (aka neuro-symbolic systems), a new sub …

Automatic taxonomy induction is a challenging task in the field of natural language
understanding (NLU) and information retrieval (IR) because it requires machine learning …

Ontologies are used to model knowledge in several domains of interest, such as the
biomedical domain. Conceptualization is the basic task for ontology building. Concepts are …

Urban analysis uses new data integration with computational methods to gain insight into
urban methodologies. But the challenge is how to populate automatically from various urban …

Данная статья посвящена исследованию методов автоматического обнаружения
сущностей (NER) и классификации семантических отношений (RC) в научных текстах …

Data engineering seeks to support artificial intelligence processes that extract knowledge
from raw data. Many such data are rendered in natural language from which entity-relation …

Modern information supports carry heterogeneous data, in such large quantities that the
traditional means of processing become obsolete and inefficient to meet today's needs. In …

Event detection (ED) is an important and challenging information extraction task, which aims
to identify triggers from unstructured text and classify them into an event type. Most of the …

Relation Extraction (RE) consists in detecting and classifying semantic relations between
entities in a sentence. The vast majority of the state-of-the-art RE systems relies on …