As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

Abstract: Personalized learning has gained significant attention in recent years in response to the limitations of one-size-fits-all approaches to teaching, particularly in areas such as programming ...

Knowledge graphs are a powerful tool for bringing together information from biological databases and linking what is already known about genes, diseases, treatments, molecular pathways and symptoms in ...

Introduction: Nature finance involves complex, multi-dimensional challenges that require analytical frameworks to assess risks, impacts, dependencies, and systemic resilience. Existing financial ...

Repository untuk sistem Knowledge Graph lengkap mencakup ontology, reasoning, graph embedding, dan question answering system untuk identifikasi hama dan penyakit pada tanaman jagung. KG/ ├── data/ # ...

Veloclade is a research prototype of a neuro-symbolic knowledge graph system. It uses clade-inspired hierarchy + embedding clustering (sentence-transformers) to control ontology growth and mitigate ...

Credit: Image generated by VentureBeat with FLUX-pro-1.1 Without data, enterprise AI isn't going to be successful. Getting all the data in one place and having the right type of data tools, including ...

A TechRadar article noted that nearly 90% of enterprise information (documents, emails, videos) lies dormant in unstructured systems. This "dark data" isn't just neglected; it's a liability. GenAI ...

Introduction: Automating the extraction of information from Portable Document Format (PDF) documents represents a major advancement in information extraction, with applications in various domains such ...