Hyperknowledge graphs
Renato Cerqueira · 2019
With the recent advances in Artificial Intelligence, the use of knowledge graphs is becoming pervasive. A new generation of AI-based applications is emerging, which relies on KGs to represent and manage knowledge. These KGs are consumed by advanced Machine Learning algorithms and reasoning engines. Despite of this increasing importance to the industry, there is a lack of methods and technologies to manage the lifecycle of KGs, especially to support reusability and maintainability. In this presentation we describe our work on the Hyperknowledge technology, which relies on the Nested Context Model to provide a flexible knowledge representation mechanism with high-level abstractions and expressiveness to enrich structure, enable reuse, and enhance interpretability.