Text mining uses computer technology to analyze uncategorized text for research and analysis purposes, finding meaning or patterns. It has applications in science, marketing, and data organization, and can be used for market research or analyzing scientific papers. It is similar to data mining but relies on special programming to search plain text.
Text mining is the process of using computer technology to filter text documents for research and analysis purposes. It is often considered to be very similar to the process known as data mining, but it relies on special programming to search uncategorized text and find meaning or patterns rather than analyzing pre-categorized database information. Text mining has many applications in areas such as science, marketing, and data organization.
The complexity involved in arranging words in the language is too extreme for computers to handle, but scientists have worked hard to improve this type of programming. Many methods have been developed to allow scientists to identify sentences and discover facts about text. This is often not the same as fully deciphering the meaning, but it allows for shortcuts that achieve many of the same goals. Text mining takes advantage of some of these techniques, and as this technology improves, it is generally expected that text mining will improve as well.
Experts use text information analysis primarily to do research on written documents. Large amounts of written data can be difficult to analyze due to the huge amount of time required. Computers can read this text much faster, but they cannot understand it. Text mining techniques allow computers to find useful trends in text, presenting data in ways that reveal new facts or allow experts to make discoveries.
An example use for this technology would be market research. Experts can analyze the search results on a product name and have the program look for phrases that express the user’s sentiment. That way they can find out how people really feel about their products in a very detailed way. They could also simply search for your product and see which phrases pop up most often, and this can help them develop new ideas on how to delight their customers.
Another use for text mining is analyzing scientific papers on similar subjects looking for new trends or agreements. This has allowed some scientists to make predictive assumptions that have proven useful in fields such as protein analysis. Some experts feel that this type of application can occasionally provide unexpected discoveries.
A process called data mining is actually quite similar to text mining, but is generally less complex because it relies on text that has already been formatted into categories. For example, the software could go through all the information for job applicants in a database, looking for trends. Text mining is harder for computers because plain text is harder to analyze than data with categories.
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