Look for Google’s Knowledge Graph to roll out across all your (US English-speaking) searches –desktop, mobile, and tablet– in the coming days.
A couple of days ago, Google Blog announced the new Knowledge Graph feature. It just appeared in my search this morning and it just may be a search game changer. The Google engineers share that it’s part of a larger plan move from being an information engine to being a knowledge engine.
After entering a search in the search box, a panel will appear on the right side of the screen designed to: suggest ways to disambiguate a search with further filtering options, summarize content, and facilitate further discovery. This new strategy may serve to remedy the missing WonderWheel issue and to help compensate for students’ limited contextual knowledge and vocabulary. It may serve to facilitate discovery around a given area of inquiry.
A Google report released earlier this year, announced that Google was switching from simple keyword recognition to the identification of entities, nodes and relationships. The new intelligent model is designed to understand real-world entities and their relationships to one another: things, not strings.
A search for Frank Lloyd Wright, for instance, will return a brief summary, photos of Wright, images of his famous projects and perhaps, most interestingly, related “things.” People who search for Wright are also looking for other notable architects. It’s a feature that may remind users of Amazon’s penchant for delivering “people who liked this book also bought or searched for this one” results.
How does it work? How does it select the stuff for that right panel?
According to the Google Blog post:
Google’s Knowledge Graph isn’t just rooted in public sources such as Freebase, Wikipedia and the CIA World Factbook. It’s also augmented at a much larger scale—because we’re focused on comprehensive breadth and depth. It currently contains more than 500 million objects, as well as more than 3.5 billion facts about and relationships between these different objects. And it’s tuned based on what people search for, and what we find out on the web.
One major component of the process of pushing content to Knowledge Graph involves exploiting the collective intelligence of Google searchers:
How do we know which facts are most likely to be needed for each item? For that, we go back to our users and study in aggregate what they’ve been asking Google about each item. For example, people are interested in knowing what books Charles Dickens wrote, whereas they’re less interested in what books Frank Lloyd Wright wrote, and more in what buildings he designed.
My search on Thomas Jefferson led me to fact box-type content with links to buildings, Thomas Jefferson University, and links to the other founders. I’d hoped it would lead to the discovery of issues during Jefferson’s presidency, his involvement with the Declaration, Lewis and Clark, the Louisiana Purchase, Jefferson and slavery.
Knowledge Graph may be a wonderful tool for guiding K12 learners through search. But it may further contribute to filter bubbling and it may obscure content for or divert searchers with more long tail interests. Could it inhibit the type of discovery it was designed to promote?
Let’s do a little field testing and see how it grows.