The Benefits of Text Mining for Border Security and Beyond

Named entity recognition

Given the advancements in computing technology, data and text can now be analyzed faster and with more precision. This makes a significant difference in various industries which rely on having access to relevant data in order to conduct business. Furthermore, it is also vital in strategic government operations such maintaining safe borders. In other words, big data analysis is central to the operation of a broad range of enterprises.

The Text Mining Process

Text mining is also referred to as text data mining and correlates with text analytics. There are four steps involved with this process:

  • Information retrieval
  • Natural language processing
  • Information extraction
  • Data Mining

After completing these steps, the goal is to have access to high-quality textual information, which in turn is used for a variety of industry-specific purposes.

How Text Analytics Benefits Border Security

Border security can be strengthened and supported through utilizing text analytics. While there are other benefits, these are considered to be the major three ways in which text analytics can accomplish this task:

  • By identifying dangers located near borders and during Visa or other types of screenings
  • By identifying potential dangers that require further investigation and/or follow-up
  • By providing forecasts of future border issues

Since these and other situations require decisions to be made based on factual information, text analytics also assists law enforcement with making positive identifications on specific individuals. Entity resolution streamlines this process. Whenever the same entity is mentioned, this process will locate and link this information across and within data sets.

If there are several semantic entities, which can occur with a similar name and other types of data, this process should be able to determine the correct semantic entity within a list of semantic entities. There are three basic tasks that are involved with semantic entities and entity resolution:

  • Deduplication
  • Record linkage
  • Canonicalization

How Text Mining Can Benefit Businesses

There are three significant ways in which business can be helped by text mining:

  • By providing more accurate insights from a variety of documents and sources
  • By providing accurate risk, compliance, and threat detection
  • By improving customer engagement and obtaining insights into what they’re thinking

Social media data analysis, or sentiment analysis, is just one area where businesses can obtain vital information. In addition to learning what their existing and/or prospective customers think of their brand, they can have increased access to other relevant information such as the types of products and/or services that interest these customers.

The Future of Text Mining

Information expands exponentially within the digital universe. The International Data Corporation reports that by 2020, this universe of information will be over 40 zettabytes. This means that on a daily basis, 1.7 megabytes of new information will have been created every second for each person. Given that less than one percent of all data that exists is actually analyzed, the International Data Corporation estimates that text mining will be able to close this gap.

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