Human behavior flows from three main sources: Desire, emotion, and knowledge. And Google seems to know this better than anyone. What made the difference between Google and other now left behind search engines was its ability to produce highly relevant results and the constant attention directed to the user’s needs and desires.
With the new Knowledge Graph technology, Google redesigns the world of search by trying not only to understand its users but also to anticipate their wishes.
What is the Knowledge Graph?
Wouldn’t it be great if Google could “understand” YOU? The words you use aren’t just words … they are entities and they refer to real things in the world.
Actually, this is possible as Google takes the concept of the traditional search engine and turns it into a knowledge engine that provides users with smarter and more relational search results. The Knowledge Graph might be one of the most revolutionary technologies used in the search industry so far. The search engine is not just a device that generates results based on specific words anymore. The search engine is now an entity that tries to understand the real-life context and concepts in order to connect the “dots”.
The Knowledge Graph is built on the Freebase graph model. The Freebase company was acquired by Google in 2010. The Freebase data remains open source, as it was before Google acquired the company. Yet, currently Freebase is closing down and merging to Wikipedia. Google launched the Knowledge Graph in May 2012 with a base of 3.5 billion facts connected up to 500 million entities. As of December 2012 the knowledge base had grown to include 570 million entities with 18 billion facts connected to them. Today, Google can recognize three times as many queries as it used to when it initially launched the knowledge graph.
This is quite an impressive demonstration of what a semantic search engine with structured data can bring to the everyday user.
How does the Knowledge Graph actually work? Let’s say you want to find information about Robert Downey Jr. Google recognizes the query related to Downey Jr. in its knowledge base and generates a panel on the right of the search results page presenting information about the actor, including images, important facts, and related searches, with links to explore the subject further. Where is this information coming from? It is a mixture between information that other users found useful and the information on the knowledge graph. Information is flexible and under continuous change so if there is a problem with the generated data, you can click on the feedback button, report a problem and the information will be modified correctly not only in Google’s database but also on Wikipedia.
Is the Google Hummingbird Update the Same as the Knowledge Graph?
The answer to this question is simple: No!
Google Hummingbird is not the same as the Knowledge Graph but the two concepts are highly interconnected.
To celebrate their 15th birthday, Google launched “Hummingbird”, the initial Google algorithm re-written and ready to be more easily expanded, claiming that Google search can be a more humane way to interact with its users and provide a more direct answer. Much buzz was made around this issue as it is said to be the biggest change Google made in the last 10 years.
The Google Knowledge Graph is a part of the Hummingbird algorithm, a system that the big G uses to understand facts about people, places and things and how these concepts are all connected.
Let’s take FC Barcelona for instance. I won’t say whether it is or isn’t the world’s best soccer team as I don’t want to cause a stir. I will say though that Lionel Messi is considered to be one of the most important players on the team as he brings a lot of added value to the sport club he plays at.
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