Entity Based Search

By Paul Morris

Note 1: For details on the schema image above visit http://ht.ly/5ca5M

Note 2: For advanced background on this topic see:

My previous posts on the Synaptic Web and the Personalised Localised Socialised Semantic Web


Google’s post on schema.org and, after reading the below, how you can utilise the Semantic web to improve your Search presence 

Facts according to Paul Matthew Morris: With Google’s Knowledge Graph, Voice Search and Google Now, Google is moving towards providing answers; in a fraction of cases even anticipating the questions. With Hummingbird Google laid the foundations for this approach to evolve further by continuing to move from text links to answers. Google now displays more precise results faster. Google is increasingly buddying up with semantics (aka entity search) focused on user intent rather than on search strings.

All this = Entity based Search.

Entity Search uses entities (people, places, things or, according to semantics, schema types), couples them with bots + machine learning + additional verified data sources, throws in a load of user intent, then lets the query cook for a fraction of a second and out pops the entity search result/ answer.

With the addition of semantics/ entities we are starting to see Search improvements that were prophesised about by Sir Tim Berners-Lee where machines are doing more than ‘merely’ indexing and instead actually understand data.

….I find this super duper interesting as Google now understands its users better than ever before. It also interests me as it has ramifications for how you optimise for Search. No longer can you rely on page titles, header tags, correctly utilised keywords on page blah, blah blah. Instead we are seeing a transition to the Personalised Localised Socialised Semantic Web I prophesised about over a year ago where the ‘semantic’ part is finally fighting its own corner and becoming an ever important part of Google’s algo.

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