To support ubiquitous AI, a Knowledge Graph system will have to fuse and integrate data, not just in representation, but in context (ontologies, metadata, domain knowledge, terminology systems), and ...

Probably the most important reason for building knowledge graphs has been to answer this age-old question: “What is going to happen next?” Given the data, relationships, and timelines we know about a ...

Document-level Role Filler Extraction exhibits a wide range of application value in natural language processing, including information retrieval, article summarization and trends analysis of world ...

Knowledge Management requires a new data model approach that unifies typical enterprise data with knowledge bases such as taxonomies, ontologies, industry terms and other domain knowledge. Franz’s ...