Text Mining with R

(This article was first published on BNOSAC - Belgium Network of Open Source Analytical Consultants, and kindly contributed to R-bloggers)

Last week, we had a great course on Text Mining with R at the European Data Innovation Hub. For persons interested in text mining with R, another 1-day crash course is scheduled at the Leuven Statistics Research Center (Belgium) on November 17 (http://lstat.kuleuven.be/training/coursedescriptions/text-mining-with-r). The following elements are covered in the course.

1. Import of (structured) text data with focus on text encodings. Detection of language

2. Cleaning of text data, regular expressions

3. String distances

4. Graphical displays of text data

5. Natural language processing: stemming, parts-of-speech (POS) tagging, tokenization, lemmatisation, entity recognition

6. Sentiment analysis

7. Statistical topic detection modelling and visualisation (latent dirichlet allocation)

8. Automatic classification using predictive modelling based on text data

 

More information on the course & the registration: http://lstat.kuleuven.be/training/coursedescriptions/text-mining-with-r

If you are interested in applying Text Mining techniques on your data, get in touch: bnosac.be/index.php/contact/mail-us

To leave a comment for the author, please follow the link and comment on their blog: BNOSAC - Belgium Network of Open Source Analytical Consultants.

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