Over the past twenty years, technology has expanded in ways that many people did not believe possible. This has now brought about huge changes within society that allow for greater communications. There are plenty of positive effects that have come directly from these types of changes. However, it is important to think about the dangers that can come from the expansion of technology as well.
Right now, the text analytics market has an estimated value of nearly $3 billion. If you find that impressive, just wait until you read about the projections for the future. Plenty of experts in this field of work involving a semantic entity believe that by the year 2020 this estimated value will double to reach $6 billion.
Name entity recognition tools, name matching tools, and name matching software are all pieces of the semantic entity. These types of products are not going to be understandable to the average person and that is why the experts in this field receive such a high level of pay. It is important for them to spend time at school studying everything about the semantic entity.
Every single day there is just about 1.7 megabytes of new information created for every person within every second. This means that over the course of the past seven years there has been a huge increase in the amount of information created. The digital universe is bound to reach 40 ZB by the year of 2020. This may sound impressive but it is also dangerous because this high amount of information can be exploited if not properly protected.
Facebook has 1.97 billion monthly active users worldwide, producing an enormous amount of data every second. This is one of the reasons why the semantic entity is important. This new waves of social media is a huge producer of data and without an understanding of the semantic entity, it can be dangerous.
The International Data Corporation, also known as the IDC, estimates that less than 1% of data is ever analyzed. Text mining can bridge the gap between the missing 99%. Text analytics can support and strengthen border security in three major ways. The first way is by being able to identify dangers near borders and at screening time. The second way involves the process of identifying potential dangers that need follow-up. Finally, it includes the ability to forecast future issues at borders.
Entity resolution is the practice of finding and linking mentions of the same entity across and within data sets. The three primary tasks involved in entity resolution are deduplication, record linkage, and canonicalization. Text mining can help businesses in three major ways: it can provide more accurate insights across a broader range of documents and sources; it can provide accurate risk, compliance, and threat detection; it can improve customer engagement by using natural language processing to generate early insights into what customers are thinking.
As previously mentioned, the expansion of the semantic entity has brought forth the method of text mining. There are four unique steps in this process. The first step involves retrieving information. The second step involves processing a natural language. The third step involves extracting information and the final step includes mining data.
In Conclusion
As technology continues to grow in our society it is so important that we continue to study this technology. Furthermore, it is even more important that we work hard to understand how this technology is changing and shaping the world around us. Technology can not just improve society but it can also potentially bring about bad things as well. These may not be intended, but that is the course of nature.
