You know what I mean? Watson does.

Watson knows the definition of “brake” – the device that stops something; or the act of stopping something. But what about the hundreds of ways that the car-driving public describes problems with their brakes to a mechanic? The brakes might “squeal,” or “judder.” Or maybe they’re “soft.” All of those descriptors could indicate a different issue that aren’t understood by a computer. Until now. Thanks to IBM Research’s Dan Gruhl, Watson can help the mechanic and the car manufacturer pinpoint the problem, based on common, even slang descriptions.

Dan Gruhl at 2015 Cognitive Colloquim

Watson Concept Expansion, on demonstration at the Cognitive Computing Colloquium in San Francisco, expanded the cognitive system’s dictionary of related words, concepts, euphemisms, and colloquialisms to better-understand context across any industry or field. Dan’s team feeds Watson unstructured data from blogs and news articles, to Twitter’s firehose, among other sources.

Then, because this is a human-machine partnership, meant to augment one another’s intelligence, the human expert begins to tell Watson what is relevant (squeaky brakes), and not (I need a break). While Watson gathers and organizes by relevance online documents and discussions about how to fix various kinds of brake problems. 

“It's a game of patterns. If I start with 'apple' and 'blackberry' in the tool, it needs to interact with me a few times before it realizes I am talking about fruits and not cell phone manufacturers.” Dan said. 

That context from such a wide and diverse source that only Watson could gather and comprehend (in seconds) gives domain experts a new way to understand their industry, brand, or product. Try it out on Bluemix, now.