Semantic Technology – Understanding the Concept

By Published April 10, 2017
Semantic Technology

Today, discussions on Semantic search technology are born out of data chaos that our governance capabilities and traditional data management are struggling under.

According to the Forrester’s Global Business Technographics® Data & Analytics Survey, 2015,

Business stakeholder satisfaction with analytics has reduced by 21 percent from 2014 to 2015.

Semantic Technology

Therefore, innovative data scientists and architects realise that semantics is the key to delivering meaning and context to information. It let us extract not only valuable business insights but more prominently personalised and scalable data.

Leading organisations identifying semantic technology as the key trend to watch in 2020 in conjunction with Artificial Intelligence and Automation. Though, still many people ask, “What is semantic technology?”

In the following blog, let’s understand more about semantic technology but in an uncomplicated way.

Semantic Technology Defined

Semantic Technology is a combination of “meaning-centred” tools and algorithms. It is capable of:

  • Categorising the data
  • Extraction of information and meaning, and
  • Auto recognition of concepts and topics.

Human language is primarily a combination of subject, predicate, and object. And this is exactly what semantic data model does and present the data in a “conceptual & contextual format.”

What is Semantic Search?

We, humans, are quite efficient at using contextual signals to comprehend questions accurately. When challenged with vagueness, our mind works amazingly well at decoding the explicit content. However, machines are not as gifted yet in this area. This is where Semantic Search comes in – it attempts to improve and augment standard search results by selecting the appropriate meaning and filtering out the noise (unrelated information) just to match the user’s intent.

A recruiting tool or HR software backed by semantic technology will always deliver the most relevant and categorised content instead of showing broadly relevant information to the original search query. Google (search engine) is the most common and relevant example of semantic search technology.

With increasingly dynamic and complex ecosystems organisations must evolve and focus on smarter and responsive systems. And, this is where semantics comes in.

In subsequent blogs, we will take our learning on Semantic Search Technology to next level.

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