Text mining is a term that are generically used in the IT world, but what exactly is text mining? Basically it is “the extraction of quantitative or qualitative information from textual sources (such as newspapers, magazines, books, web pages, receipts, manuals, etc.) by employing the computing power of computers.” It is very similar to “text mining”, which is also known as “digital text mining,” and is the process of extracting useful data from non-textual sources. In fact, it’s nothing more than “digital mining” in the legal sense.
The most common people to ask what is text mining is the financial industry. For example, loan officers have to be able to extract useful insights from bank statements, credit reports, and other financial documents. Likewise, human resources personnel need to be able to extract data from employee performance evaluations and interviews. Human resource department executives also need to be able to “mini track” key employees to make sure they’re on track and meeting goals.
So, how does this work? Basically what is text mining involves using “natural language processing tools” (that is to say software programs) to extract useful insight from large amounts of structured text. Natural language processing tools are a bit like computers in that they can process unstructured text and then extract relevant information. The most popular types of natural language processing tools are:
Text mining and text analytics go hand in hand, and the use of both can be applied to nearly every aspect of any business. The only thing you need to do to reap the full benefits of what is text mining is to invest in the right tools and to train employees appropriately how to use them. Fortunately, just about every business is now using some form of text mining or text analytics. This is because of the benefits that come from using it. Companies of all sizes can save money, provide better customer service, and gain a competitive edge over their competition.
In order to understand what is text mining, you have to first understand what text mining is not. Structured analysis is when a company manually takes information from a variety of different sources in order to help improve their business. This may include gathering data from an entire company’s intranet, looking for patterns that may indicate certain processes are ineffective and even analyzing a company’s website. Textual analytics on the other hand is analyzing unstructured text data and comparing it to certain characteristics of unstructured text such as company logos, product descriptions, and other unique features found in written material.
There are a few main benefits to what is text mining techniques. One benefit is the ability to receive very insightful and valuable information through text mining. It is through this method that companies are able to receive detailed insight on what customers are looking for, what they are looking for in products and services, and what specific words people used to search for those products and services. Since this is an untapped resource, companies that utilize these analytic methods are able to save a substantial amount of money by cutting out what is often considered unimportant or irrelevant data, and focusing instead on what is important.
In order to make this analysis work for your business, there are a few things to keep in mind. First, in order to receive the most insightful insights, you need to make sure that you collect the right types of data. If the information you are collecting only comes from websites that sell products or services, then you are limiting your potential to gather useful data. As an alternative, if the unstructured text comes from articles, blogs, or even personal blogs written by customers, then you will be even more limited in what you are studying. However, the key to maximizing what is text mining techniques is to know which types of information are better suited to be analyzed. This is why businesses should make sure to collect as much data as possible and then use a variety of analytical software programs to determine what types of information are relevant and what types are useless.
The ability to analyze large amounts of structured data, along with the ability to utilize advanced text mining techniques, has made this tool an integral part of business intelligence tools used by some of the largest companies in the world today. For small businesses, however, it can be difficult to invest the time necessary to use this powerful analytical program, and as a result many small businesses simply do not take advantage of what text analytics can offer. However, with the right tools and a willingness to invest in the time it takes to understand how text analytics works, any small business can benefit from the analytical tools offered through text mining techniques.