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Google’s Knowledge Graph – has search just changed forever?

Late last week, Google representatives unveiled a significant enhancement to the company’s ubiquitous search engine. They’re calling it the “Knowledge Graph” and claiming it will support “more intelligent…

Semantic search is about recognising the meaning of words, not just the words themselves. Chris P Jobling

Late last week, Google representatives unveiled a significant enhancement to the company’s ubiquitous search engine. They’re calling it the “Knowledge Graph” and claiming it will support “more intelligent searching for real-world things on the internet”.

And while it might be a while before Australian users have access to the Knowledge Graph, the US roll-out is expected to begin in the coming days.

So what is it? How does it work? And will it change the way we find information online?

According to the company, the Knowledge Graph encompasses three new features:

“Find the right thing”

If your search term is ambiguous and has multiple meanings, the new interface will help to narrow your search. For instance, if you search for “Madonna” a panel pops up allowing you to choose between the religious icon and the pop star.

Click for larger view. Google

“Get the best summary”

Search results will now include additional key facts about the topic being searched. So if you search for “Frank Lloyd Wright”, Google’s Knowledge Graph knows that your search text refers to a famous person, and so that person’s birth date, death date, education, spouse’s and children’s names are all displayed.

Click for larger image. Google

“Go deeper and broader”

Search results will now also include key relationships to other resources on the web. In the case of Frank Lloyd Wright, the Google Knowledge Graph knows he’s a famous architect, so the results include links to buildings he has designed and other significant architects from the same era.

Click for larger image. Google

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.

Moreover, the Knowledge Graph can identify and retrieve connections to related “things”, such as people, objects, places and events. For example, in the case of Frank Lloyd Wright, the search returns links to buildings he’s designed and other famous architects from his era.

Such relationship or “knowledge” graphs provide an intuitive interface for understanding a topic, its context in the wider web (and world) and for triggering new lines of enquiry.

So how does this technology work?

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. For instance:

Dr Strangelove {film} has_director {property} Stanley Kubrik {person}.

Using the property “has_director”, the above example links the entity Dr Strangelove (of type “film”) with the entity Stanley Kubrick (of type “person”). The Freebase knowledge graph is built on millions of these connections, having been contributed through crowdsourcing, much like Wikipedia. Consequently the database will continue to grow and improve over time.

Freebase’s approach builds on “semantic web” technologies and the more recent Linked Open Data movement.

The semantic web is a World Wide Web Consortium (W3C) initiative that aims to provide meaning to objects and pages on the web. This is achieved through standardised, machine-processable metadata descriptions plus persistent unique identifiers or URIs (uniform resource identifiers).

Quite simply, the semantic web is about creating a “web of data” from an otherwise-unstructured jumble of web pages from all around the world.

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.

In that vision, humans, computers and software agents on the web automatically and seamlessly communicate and interact together intelligently. In the article, Berners-Lee gives the example of a semantic-web-enabled microwave oven consulting the frozen food manufacturer’s web site to retrieve optimal cooking parameters.

Many see Google’s “Knowledge Graph” as the coming-of-age of the semantic web. Finally, semantic web technologies are validated by their underpinning of the world’s biggest search engine, used by millions daily, to provide intelligent, contextualised search results.

So where is this heading in the future?

As mentioned, the Knowledge Graph on Google Search will be initially rolled out only in the US but other countries, including Australia, will likely follow (depending on the popularity of the service).

According to Google, a tailored version of the Knowledge Graph for smartphones and tablets will also be available soon.

Only time will tell whether users love or hate the new semantic search features. But even if users don’t like it now, it’s highly likely that semantic searching will be a feature of search engines in the future.

Over time, the data underpinning the Knowledge Graph will grow, enabling even smarter, richer search results. In addition, Google has the huge advantage of being able to combine its existing data on who searches for what, with Freebase’s massive corpus of linked open data, to identify the most sought-after facts or relationships that should be recorded for each entity.

This combination will lead to the killer Google app – a search engine that delivers both personalised and contextualised semantic search results.