As we’ve explained in many blogs and 5-minute guides, a cognitive search platform should combine AI technologies such as natural language processing, machine learning, and knowledge graphing to deliver a contextualized search and discovery experience without compromising security. Those technologies can turn ordinary search into something much more powerful and transformative for any organization.
Today’s business users don’t search for documents that may have the information they seek buried within, instead they ask their systems for answers. This shift in attitude is a key driver behind the move to cognitive search.
These days, there’s pretty much a trade show for everything — and predictive analytics is no exception. The most recent stateside edition of Predictive Analytics World™ took place in Chicago in June of this year. And predictive maintenance occupied a prominent place on the agenda. One presentation concerned failure and fault detection for Rolls Royce.
Remember the frustrations of key word search? If you need a refresher, just check out If Google Was a Guy. It’s funny—in a way that makes you kind of squirm in your seat. Of course, in the early days of search engines, power searchers used Boolean query operators. We have George Boole, 18th-century English mathematician, to thank for that.