GitHub

Agentic ontology-assisted framework for semantic triple extraction

OntoCast is a framework for extracting semantic triples (creating a Knowledge Graph) from documents using an agentic, ontology-driven approach. It combines ontology management, natural language ...
IEEE

Ontology Synthesis Using Semi-Automatic Semantic AI Using Deep Learning and Reinforcement Learning

Abstract: The need for automatic ontology modeling has become particularly significant in the era of Web 3.0, where ontologies serve as the structural metadata backbone. Despite their importance, ...
northpennnow

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
The Lancet

When to and when not to use machine learning in risk prediction models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...
IEEE

Ontology-Driven Pipeline for the Automated Generation of Multimodal Datasets for Supervised Learning in Natural Hazard Models

Abstract: Effective machine learning for natural hazard prediction and monitoring depends on timely access to high-quality, event-specific datasets and models capable of adapting to evolving ...