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How to Expedite Data Analysis With Text Mining and Entity Matching Applications

Written by admin on . Posted in Advanced geotagging, Big data analysis, Named entity recognition tools

Sentiment analysis

Given the vast amount of data that exists within the digital universe, there’s a pressing need to analyze it. The International Data Corporation predicts that by 2020, the digital universe will contain over 40 zettabytes of data. While it does seem like a daunting task to analyze what amounts to 1.7 megabytes of new data per second for every person, there are solutions.

According to the International Data Corporation’s estimates, less than one percent of the data that exists has been analyzed. In order to analyze the remainder, which amounts to roughly 99%, text mining is a solution. When businesses use text mining software, it can be of benefit to them in three significant ways.

When it comes to documents and other vital sources of information, text mining can provide more accurate insights across a broader range of these items. Text mining can also provide increased accuracy with risk, compliance, and threat detection. Furthermore, it can also improve the customer experience and engage these customers by employing natural language processing. As a result, early insights into what customers are thinking can be generated. This is also referred to as sentiment analysis.

There are four basic steps involved within the text mining process:

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

Entity matching applications are an important tool for determining entity resolution. For example, when considering that Facebook has 1.97 billion worldwide users that are active on a monthly basis, an enormous amount of data is produced every second by these users. In order for businesses to make sense of this data, topic tagging is a useful tool.

When Facebook users make comments on specific brands, services, and events, for instance, this data can be located and linked through the process of entity resolution, or entity matching. There are three main tasks involved in this process:

  • De-duplication
  • Record linkage
  • Canonicalization

Entity matching applications have the capacity to catalogue and analyze unique company brands and names as well as other important information. This includes dates, events, and the names of people.

Given the incredible amount of data that has been created and will continue to be created, it makes sense for businesses and other types of organizations to explore these types of tools. Since text mining and entity matching applications can expedite the analysis of data vital to conducting and expanding business, it makes sense to learn more about how this could benefit your enterprise.

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