From the course: Data Science Foundations: Data Mining in R

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Text mining overview

Text mining overview

From the course: Data Science Foundations: Data Mining in R

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Text mining overview

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- [Instructor] Text is not like other data and when it comes to data mining, it poses some very special challenges. Those challenges include things like the fact that there are enormous quantities of text. There is so much open text in terms of books, in terms of news articles, and in terms of social media. It's completely overwhelming. Also it's enormously variable. There are so many different words. There are so many phrases. There are so many misspellings and colloquialisms. There's a lot there. What this all tells you also is that it's unstructured. It doesn't fall into nice little rows and columns of data, it just kind of is what it is, that makes it a very difficult thing to mine for. And when you're mining for data, you're trying to get value. You're trying to get more than like Hamlet saying that he is reading words, words, words, you're trying to get meaning and actionable insight out of your data. Now…

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