Expand your own Knowledge Vault with Google

Google is continually looking to discriminate between websites, which has often caused unrest amongst peers within the world of SEO. However, the emergence of semantic search means that digital marketers now have to extensively strategies on how the information that a website presents is interpreted by search engines, in order to comprehensively provide the user with the information that they are looking for.

The Knowledge Graph and semantic search

Google’s semantic network, as of 2012, contained a total of over 500 million objects and more than 18 billion facts pertaining to the relationships between words/objects that are utilised to understand the meaning of search terms entered into the query box. Such an extensive network has taken years to develop and stems from the operational methods of ‘answer engines‘, such as Ask Jeeves, where the results are aimed at answering a specific question that Jeeves was asked.  However, all of this tedious work has entirely revolutionised the selection method behind displaying the most relevant organic search results and, in turn, continues to satisfy the inherent human desire of harnessing new information in the simplest of ways.

Over recent years, Google has shifted much focus onto semantic search in order to improve search accuracy by trying to understand the intentions of the search engine users, including the contextual meanings of the used terms. The Knowledge Graph was designed to provide key information and statistics about semantic search terms regarding a person, place or thing, without the user even having to click on one of the organic listings. Much of this information is derived from Wikipedia, but there are many other sources/links that contribute to this as well.

The introductory video (shown below), created by Google, explains the functions of the Knowledge Graph and the reasons behind its conception.

Furthermore, in a 2012 blog post by Google SVP, Amit Singhal, he proclaimed that;

“The Knowledge Graph also helps us understand the relationships between things. Marie Curie is a person in the Knowledge Graph, and she had two children, one of whom also won a Nobel Prize, as well as a husband, Pierre Curie, who claimed a third Nobel Prize for the family. All of these are linked in our graph. It’s not just a catalog of objects; it also models all these inter-relationships. It’s the intelligence between these different entities that’s the key.”

Wikipedia detriment?

Also in 2012, Google rolled out updates to the Knowledge Graph by introducing this in seven more languages, but was unfortunately met with some dismay as several news websites reported that this implementation has inadvertently caused a decline in page views of Wikipedia pages (see below).

However, this added intelligence enables users to access a wealth of information far more easily without the need to click on several search results to piece together an answer. As time surpasses, the further expansion and diversification of this functionality will inevitably mean that finding and obtaining information will be a much less-time consuming task.

So what does this mean for the future of semantic search?

The future of semantic search seems particularly auspicious for search engine users, as Google continues to update many different areas of the Knowledge Graph. More recently, Google announced a new initiative called the Knowledge Vault. This knowledge base contains over 1.6 billion facts that have been automatically collated from the internet in addition to storing data predominantly derived from the Knowledge Graph and its corresponding sources.

Despite sharing similar data, the fundamental difference between the two are through the accumulation of the presented facts. One one hand, the Knowledge Graph extracts most of the information from reliable and trusted crowdsourcing sites such as Wikipedia and Freebase. Whereas, the Knowledge Vault autonomously gathers facts from across the web taken from a mix between high- and low-confidence sources, with the utilisation of machine learning to rank them.

It may be soon than people may think when Google eventually provide conclusive and comprehensive answers to semantic search terms, particularly if the historic updates are anything to go by. Adversely, this may also mean that frivolously browsing the web for the information you require will become a much more of a futile activity.

Further expansion to Google’s Knowledge Graph

Last week, a spokesperson of Google recently announced to Venture Beat that they have now expanded the Knowledge Graph to incorporate the capability of recognising video games, stating;

“We always want to help people find the best answers to their questions – fast. With today’s update, you can ask questions about video games, and (while there will be ones we don’t cover) you’ll get answers for console and PC games as well as the most popular mobile apps.”

Anything from mobile app games to PC and console games, has now been included within the Knowledge Graph (see below) and the best feature of this is that this new inclusion is that it is not specific to the UK.

As demonstrated by this screenshot of a search for console game ‘Destiny’ (above), the knowledge graph pulls through a wealth of information about the game itself and provides a host of links to various other sources regarding the game. So if an inexperienced gamer, persay, was perusing the internet to find out more information about this game, then all of the key facts are clearly displayed in the right column. The addition of the “People also searched for” section is an effective method of allowing the search user to easily navigate to other pages and other games.

As Google continues to update both the Knowledge Graph and Vault, the future looks very bright for semantic search and it’s useful to consider these type of search terms in any SEO campaign. Semantic search is expanding, but is your digital marketing strategy equipped for it?