How Text Analytics are Important for Border Security and Business

Sentiment analysis for brand reputation

Concept extraction software, advanced geotagging, and other forms of big data analysis are part of the effort to improve border security and provide value for businesses. Here are the important facts to know about concept extraction software, opinion mining, name matching software and more:

How is Text Analytics Useful For Security?

Named entity recognition or concept extraction software can greatly improve border security. All types of text analytics allow for dangers to be identified near the border and at the time of screening. It also lets government agencies forecast future issues and identify potential dangers so that they can be followed up.

How Can Text Mining Help Businesses?

There are three important ways that text analysis software tools and other forms of concept extraction software can be of enormous help to any business. They are able to provide a company with more accurate insights when looking at a very broad array of sources. They also help to improve customer engagement through the use of natural language processing. This allows the company to get insight into customer opinions and early on. Finally, text mining allows for accurate risk detection, as well as compliance and threat detection.

Is Text Being Analyzed Already?

Only some text is currently being analyzed. The International Data Corporation (IDC) has estimated that only about 1% of all data is really being analyzed. It is text analytics tools that can bridge this gap and provide access to the other 99%. Currently, the market for concept extraction software and other types of text analytics stands at an estimated three billion, and that market is set to reach double that by 2020. The amount of data being created is astronomical. The IDC again estimates that by 2020 the size of the digital universe will be 40 ZB. That’s as much as if there were 1.7 MB of new data for every person on the planet every second of the day.

What Goes Into the Process of Text Mining?

There are four important steps in the process, all of which can be automated by the right type of text analytics software engine. The first step is the retrieval of information. Then that information is reviewed using natural language processing. Important or relevant information to the entity conducting the text mining is then extracted. Finally, text mining ends with specific data extraction.

The data sets that governments and business have to work with in the modern world are far too large to ever be analyzed by hand. Concept extraction software and big data text analytics are capable of handling this data, even unstructured data, and turning it into valuable insights that keep us all safe and our economy moving forward.

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