→ knowledge graph scaffold
A Knowledge Graph represents a collection of interlinked descriptions of entities (nodes) – real-world objects, events, situations or abstract concepts. The nodes are connected to each other by “edges”, that define the relationship between the two nodes.
Ingentium has created a knowledge graph scaffold from existing information sources. At this time there are more than 35 node types, with over 34M nodes in the scaffold. There are more than 20 edge types, with more than 17M edges in the scaffold. See details on the scaffold below.
Ingentium uses information from its knowledgebases and other sources to create knowledge graphs that can be focused on specific disease areas and health topics. We use a novel big data cyberinfrastructure technology, leveraging machine learning and semantic analysis, to aggregate and refine the latest news and information into focused, disease-specific knowledge bases. We use natural language processing (NLP) and semantic predication to build contextualized knowledge graphs using learned content. Our knowledge bases are also used to deliver media to patients, physicians, and the medical research community in our Health Magazines, a component of the Ingentium Health Network, which updates daily. We update our knowledge graphs on a regular schedule, usually weekly.