It’s time you differentiate between “Apple is awesome” and “Apples are sweet”

  • BLOG
  • July 29th, 2019

Wondering about the title? The language of business is complex and constantly changing. A new way to segregate the story of “Apple” (a company) from apples (fruit) is needed.

With the increasing amount of digitization, text mining and analytics have increasingly become popular analytical tools for businesses. However, Text analytics can support only to a certain extent, since it analyzes information using user defined rules. The traditional text representation method “Vector Space Model” has several shortcomings when it comes to capturing text structure and the semantic information of text content.

Text mining along with Graph analytics can prove to be a powerful analytical tool for organizations.

Text analytics can help give structure to the natural language to extract meaning from free flowing information which can then be stored in graph databases. And, Graph analytics helps in visualizing relationships between people, objects, or nodes in a network. Interestingly, Graph analytics can be used to model relationships and processes in physical, chemical, biological or information systems, which widens its application. Graph analytics, as a powerful means of semantic metadata management to draw insights can be used to fulfill users’ search demands.

Let’s see what a typical text mining process looks like and where can Graph analytics fit:

Because these relationships that exist, this information can be represented using a graph and inferences can be drawn about some of these facts.

Graph analytics and Text analytics, gives organizations an opportunity to delve into not just the deeper insights but also divulge the hidden interconnections between data. It can enable businesses to get new, more actionable, more relevant answers and solutions to many unanswered questions.

When used in collaboration Graph analytics and Text analytics can change the way organizations approach analytics. However, organizations will have to identify aspects in their businesses where they can reap the immense benefits of this collaboration along with other analytical tools.

To know more about graph analytics, check out our infographic on graph analytics