Environmental changes can profoundly impact the performance of artificial intelligence
systems operating in the real world, with effects ranging from overt catastrophic failures to …

We propose the LLMs4OL approach, which utilizes Large Language Models (LLMs) for
Ontology Learning (OL). LLMs have shown significant advancements in natural language …

Ontology learning aims at reducing the time and efforts in the ontology development
process. In recent years, several methods and tools have been proposed to speed up this …

Our OntoLearn system is an infrastructure for automated ontology learning from domain text.
It is the only system, as far as we know, that uses natural language processing and machine …

Ontology Learning greatly facilitates the construction of ontologies by the ontology engineer.
The notion of ontology learning that we propose here includes a number of complementary …

Ontology learning and population: bridging the gap between text and knowledge Page 1
ONTOLOGY LEARNING AND POPULATION: BRIDGING THE GAP BETWEEN TEXT AND …

Abstract Domain ontologies play an important role in supporting knowledge‐based
applications in the Semantic Web. To facilitate the building of ontologies, text mining …

The present invention is a method and apparatus for a Vital Text Analytics System (VTAS)
that improves the comprehensibility and fidelity of technical specifications, instructions …

Abstract Information and communication infrastructures underwent a rapid and extreme
decentralization process over the past decade: From a world of statically and partially …

Ontologies are a key element of the Semantic Web. They aim to capture basic knowledge by
providing appropriate terms and formal relationships between them, so that they can be …