Graphs and Knowledge Management have gained significant visibility with the rebirth of artificial intelligence and emergence of cognitive computing. By combining artificial intelligence, big data, semantic technologies, graph databases, and dynamic visualizations, we will discuss deploying a Cognitive Probability Graph concept as a means to help predict future events across numerous types of industries.

Knowledge creation via Cognitive Probability Graphs stems from the capability to combine the probability space (statistical inference on patient data) with a knowledge base of comprehensive industry terminology systems. Cognitive Probability Graphs are remarkable not just because of the possibilities they engender, but also because of their practicality. The confluence of knowledge via machine learning, semantics, visual querying, graph databases, and big data not only displays links between objects, but also quantifies the probability of their occurrence. We believe this approach will be transformative across numerous business verticals.

During the presentation we will describe the Cognitive Probability Graph concepts using graph technologies combined with Hadoop, along with analytics via R, SPARK ML and other AI techniques. We will cover the commercial applicability to several domains including examples.