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Topic Modeling is a form of text mining that looks for patterns of words that tend to occur together in documents, then automatically categorizes those words into topics. Older text-mining techniques require the user to come up with an appropriate set of topic categories and manually find hundreds to thousands of example documents for each category. This human-intensive process is called supervised learning. In contrast, topic modeling, a type of unsupervised learning, doesn't need suggestions for an appropriate set of topic categories or human-found example documents.


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