A Quantitative Business Case for Structured Content
A popular misconception is that content in a document is unstructured data and, as a result, software typically treats a document as a “black box” with no visibility to the meaning of the information contained within. By using natural language processing and machine learning automation one can turn a document into a collection of structured content components with metadata describing the subject matter of each. In addition, the similarity in meaning between content components can be gauged and used to map information as it travels through a document collection. As a result, turning unstructured data into structured content. For many, authoring is the first thing that comes to mind when one talks about “structured content”. This webinar will present in quantitative terms the business value of having structured content, regardless of how it was authored.