{"id":50138,"date":"2019-08-15T01:00:23","date_gmt":"2019-08-15T00:00:23","guid":{"rendered":"https:\/\/www.clickworker.com\/?p=50138"},"modified":"2022-07-25T17:34:38","modified_gmt":"2022-07-25T16:34:38","slug":"text-classification","status":"publish","type":"post","link":"https:\/\/www.clickworker.com\/customer-blog\/text-classification\/","title":{"rendered":"Text classification – areas of application on the Internet"},"content":{"rendered":"
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There are billions of websites with countless texts on the Internet. This makes it difficult to keep track of them. Text classification is a method that provides an overall view and structures the offer. Which application areas are there for text classifications in the World Wide Web?<\/p>\r\n\r\n\r\n
The amount of data on the Internet is so large that filtering by human experts alone is impossible to conceive. The more information is spread on the Internet, mainly in text form, the greater the need for machine analysis, sorting and classification. Examples: <\/p>\r\n\r\n
\r\nMachine support is an effective aid for classifying texts. Artificial intelligence plays an increasingly important role here.<\/p>\r\n\r\n
Artificial intelligence shows that it is also useful in the classification of texts. In this case, the knowledge acquisition of the algorithms is based on training data that are already pre-classified. New text documents are gradually compared with these training data. The principle of trial and error provides increasingly accurate results.<\/p>\r\n\r\n
The problem with the analysis of words lies mostly in filtering out the irrelevant features. One approach for this is so-called stemming \u2013 each word is systematically traced back to the root of the word. By excluding superfluous features, the runtime of the programs is considerably reduced. <\/p>\r\n\r\n
When classifying texts, not the meaning of individual words ultimately matters, but the context in which they are used. <\/p>\r\n\r\n
For example:<\/strong> Even if the word flower does not appear in a text, the text nevertheless deals with the topic if words relating to the environment are used frequently, for example roses, tulips, garden or fertilizer. <\/p>\r\n\r\n\r\n