What is a knowledge graph?
A knowledge graph acquires and integrates information into an ontology and applies a reasoner to derive new knowledge.
(Lisa Ehrlinger and Wolfram Wöß – University of Linz in Austria)
The term knowledge graph has been frequently used in research and business, in close association with Semantic Web technologies, linked data, web-scale data analytics, and cloud computing. At SEMANTiCS, a few years ago, a research paper titled “Towards a Definition of Knowledge Graphs” by the Institute for Application Oriented Knowledge Processing of the University of Linz was presented to propose a definition of the knowledge graph that focuses on data modeling and reasoning.
The popularity of the term is strictly connected with the launch of the Google Knowledge Graph in 2012, and by the introduction of other large databases by major tech companies, such as Yahoo, Microsoft, AirBnB and Facebook, that have created their own “knowledge graphs” to power semantic searches and enable smarter processing of data.
In the context of Semantic Web, a knowledge graph is a way of representing knowledge. In short, you start from a few triples and those triples are put in relationship to build a graph. For instance, let’s have a closer look – using Semantic Web technologies – at the Apology of Socrates entity on this blog:
As you can see we have a set of triples that tell us a story: The Apology of Socrates, also known as Apology of Socrates is about Socrates, has been written by Plato and mentions the concepts of Daemon and Socratic Dialogue.
A knowledge graph doesn’t speak any particular language. Language is human; a knowledge graph gets expressed in open linked data, which is the language of machines.
Imagine your entire website built upon a large knowledge graph made of all the metadata that describes the thing that you write about. That knowledge graph becomes part of a larger graph that comprises the new web. That is the power of Semantic Web.
Popular Knowledge Graphs
There are many different types of knowledge graphs developed by different companies that are used for different purposes. While many companies use an internal or smaller knowledge graph for online functions, some of the biggest ones are being used by many people all over the world. Below lists a selection of some of the largest knowledge graphs to date from Microsoft, Google, Facebook, IBM and eBay.
|Developer||Purpose & Function||Stage of Development|
|Microsoft||Uses KG for the Bing search engine, LinkedIn data & Academics.||Actively used in products|
|KG is used as a massive categorization function across Google’s devices and search engine.||Actively used in products|
|Develops connections between people, events and ideas, mainly focusing on news and||Actively used in products|
|IBM||Provides a framework for other companies and/or industries to develop internal knowledge graphs||Actively used by clients|
|eBay||Currently developing a KG that functions to provide connections between users and products provided on the website.||Early Stage of Development|
Most people conducting SEO will tend to focus on the Google Knowledge Graph as it’s the most frequently used and relevant knowledge graph for SEO. As Google, being the most popular search engine and the driver behind a lot of search engine innovation, it’s important to focus on developing entities and contributing to their knowledge graph. Microsoft’s knowledge graph is still something to pay close attention to, as while not as many people use Bing, plenty of people do use Microsoft’s services, including LinkedIn. So while Google may be the primary focus of SEO and entity development, it’s important not to forget about Microsoft. Thankfully, they both use schema markup, so developing entries for both of them shouldn’t be too difficult.
Other knowledge graphs may be useful in SEO in certain circumstances. For example, Facebook’s knowledge graph might be useful for branding, local businesses, and people hosting events. IBM’s knowledge graph might be useful in working within the internal knowledge graphs of other companies but may still hold value for SEO. The same goes for eBay’s knowledge graph, though it is more uncertain as their knowledge graph is still in the early stages of implementation and development. There are also many more knowledge graphs not listed above that are used by many publishers and developers across many different platforms.
The Development of Knowledge Graphs
The first knowledge graph was launched by Google on May 12th, 2012 as a means of enhancing the value of knowledge provided by the search engine. By using structured data through schema markup, a user could provide information in HTML code that could then be picked up and used in knowledge cards and the newly developing featured snippets. What this meant is that websites could gain traction by helping Google provide answers to queries directly in the SERP.
Other search engines and companies began to also develop knowledge graphs. Some, like Microsoft, developed them for a similar purpose to Google; while others, like Facebook, have been developing them for different reasons, namely people and events as opposed to general knowledge about the world. When it comes to SEO, schema markup has expanded to be compatible with Yahoo and Microsoft Bing in addition to Google, making it easy to provide markup for the top search engines.
Today, knowledge graphs are being utilized in many companies and provide a knowledge network for a variety of different functions. As knowledge graph technology continues to develop and evolve, it faces many new challenges. Issues like changing knowledge, managing identities, as well as concerns regarding security and privacy are all ongoing issues facing many knowledge graph developers. These issues will continue to be a challenge for some time to come and perhaps more so in the future.