From Information to Knowledge. Googles Knowledge Graph

Google has announced it is enhancing it’s search engine – moving from an “information engine to a knowledge engine”.  It looks pretty cool.  While not yet available everywhere (those of us in Australia will have to wait a while) it is being rolled out in the US.  As The Conversation explains very well:

The aim is to provide a more intelligent search engine – one that isn’t based on simply matching strings (a sequence of characters, such as a word) to single web pages. Instead, the Knowledge Graph will “understand” what you’re searching for and provide more relevant and precise information.

…About a year ago, Google acquired Freebase, an “open shared database of the world’s knowledge”. It’s a repository of structured knowledge describing over 20 million entities, each with a unique identifier, a type (people, place, book, film, building) and a set of properties (e.g. date of birth for a person, latitude and longitude for a place).

Each entity is represented by a topic node in the massive graph that underpins the database. Properties can be used to specify relationships between entities and topics.

Freebase’s approach builds on “semantic web” technologies and the more recent Linked Open Data movement. The Semantic web has been driven to a large degree by Tim Berners-Lee, the inventor of the World Wide Web. While the concept of the Semantic Web has been around for more than ten years, the vision described in a 2001 Scientific American article by Berners-Lee has largely been unrealised.

Google has tried many different initiatives to varying degrees of success – such as Google Wave, Google Health, Google+, but where Google’s forte is search and this initiative will, I hope, mean that we not only get more information from our searches, but also learn more.