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 to analyze scientific articles and market research. Text mining is more complex than data mining, which analyzes pre-categorized data.
Text mining is the process of using computer technology to sift through text documents for research and analysis purposes. It is often thought 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 fields like science, marketing, and data organization.
The complexity involved in organizing words in language is too extreme for computers to handle, but scientists have worked hard to improve this type of programming. Many methods have been developed that allow scientists to identify sentences and discover facts about text. This generally doesn’t equate to deciphering the meaning completely, but it does allow for shortcuts that achieve many of the same goals. Text mining takes advantage of some of these techniques, and as this technology improves, text mining should improve as well.
Experts use the analysis of text information primarily to research written documents. Large amounts of written data can be difficult to analyze due to the enormous amount of time required. Computers can read this text much faster, but they can’t 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 of using this technology would be market research. Experts could analyze search results on a product name and have the program look for phrases that express the user’s sentiment. This way, they can find out how people actually experience their product in great detail. They could also just search for their product and see which phrases pop up the most, which could help them develop new ideas on how to please their customers.
Another use of text mining is to analyze scientific articles on similar topics in search of new trends or agreements. This has allowed some scientists to formulate predictive hypotheses that have proven useful in fields such as protein analysis. Some experts believe that these kinds of applications could eventually lead to unexpected breakthroughs.
A process called data mining is actually quite similar to text mining, but it’s generally less complex to do because it’s based on text that’s already been formatted into categories. For example, the software could look at all the information for candidates in a database for trends. Text mining is more difficult for computers to do because pure text is more difficult to analyze than categorized data.
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