When I went to Text Analytics World in San Francisco earlier this month, I was struck at how many of the presenters, particularly consultants, ended their talks describing future directions of text analytics as something that sounded so familiar.
They described what would be possible once there's advanced maturity in ontologies, the breaking down of siloes, entity and relationship resolution by multiple methods, and automated linking of it all together into semantic network models of knowledge: flexible exploration of the relevant. They made it sound like a bit of a stretch, almost pie in the sky, but what they briefly described as this destination was curiously similar to what was shown concretely in the last presentation of the conference, my own.
I spoke about the interconnectedness of information: information found in different ways, extracted using many different NLPs, from documents, from structure, from the semi-structured, as well as from databases. My presentation showed how a technique Cambridge Semantics pioneered, known as semantic overlay, empowers business users to easily explore auto-connected relationships. These novel compound relationships could not have been found using only a single NLP technology, but have only been found by making disparate language technologies cooperate together without prior coordination, using Anzo Unstructured. As the use case I showed was our industry-lauded financial compliance surveillance solution, compliance officers are the ones directly benefiting with these richer tools in their daily workflows.