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What is Semantic Search?

There is a lot of confusion when it comes the definition of semantic search. Some of it comes from the formalities of the definition of semantics commonly associated with linguistics and some of it comes from the misunderstanding that arises the moment the words “structured data” are mentioned.

In truth semantic search has a little to do with both and a lot to do with the four vectors that drive Big Data across the web:

• Volume is about processing massive amounts of data and extracting unique meaning from it.

• Velocity refers to the speed at which critical data comes in and how quickly is must be analyzed and processed.

• Variety is required as well, as many different types of data must be handled, such as audio, video, and text.

• Veracity is about the need to validate the accuracy of the data being processed.

To understand it better it helps to take things from the beginning and the true beginning for semantic search started on August 30th, 2013 when Google quietly rolled out Hummingbird.

The change, which was announced on the eve of Google’s 15th birthday, almost a month later, completed a long journey for Google to turn search into more than a blind fishing expedition where those who created content and those who looked for it continually strove to second-guess each other’s keywords and connect.

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