Text Analysis Software – How it Works and Where it is Being Applied Today

In its simplest form “Text Analysis” is the means of obtaining and classifying data from text-based data sources in an automated way. It is also often referred to as “Text Mining” which essentially shares an identical meaning.

In the corporate domain, data is now the new global currency, and with so much data in existence today it is impossible to manage in an efficient way without leveraging smart machines and advanced software programs. Text Analysis bots are able, to process vast swathes of information, tagging, sorting and indexing it at the same time. Resulting data can be classified by category, positive or negative sentiments together with many other methods.

Text Analysis software programs rely on advanced machine learning techniques to function. During development machines are taught to understand segments of text by engineers. Based on the experience learned they begin to understand, which text strings and patterns should be given preference over others and like humans they become better, and better as they gain more experience.

The Text Analysis process itself combines many different technological principles when interpreting an element of text. Things that are assessed include: word frequency count, collocation (words that appear together), concordance (context), text classification, sentiment analysis, and many more. Each of the assessment techniques are based on a series of defined principles, and the Text Analysis engine uses input from all these sources to make an informed decision about the text being processed.

At Search365 our Knowledge Miner technology is at the forefront of the Text Analysis field. Our engineering team working closely with experts from Microsoft are transforming the way data is being managed for some of the largest Enterprise businesses here in Australia.   

Enterprise Search technologies (specifically Text Analysis elements) are being applied to many different aspects of operations today. These include: Brand Monitoring, Customer Service, Ticket Analytics & Routing, Analysis of NPS Results & Surveys, Knowledge Management, Sales & Marketing, and many more. For those interested in exploring this subject in greater detail please visit us online and Get the Demo.

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