Website of Professor Dr. (UoP) Bernd Heesen

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Text Mining

The Learning objective is to understand the value of language for the human-computer (voice recognition, optical character recognition, text recognition), computer-computer (automatic translation & text analytics), and computer-human communication (chatbots, automatic document creation, automated speach response via virtual assistants...). The foundation for this are data science and linguistics (Natural Language Processing = NLP).

Students learn to use the programming language R and how to perform Text Mining using NLP. How to prepare text analytics via string manipulation and keyword scanning and how to present findings in form of network diagrams word clouds and term frequencies are covered as well as sentiment scoring, polarity, subjectivity, and emoticon use.

Advanced analytics include hidden structures, document classification, predictive modeling and world mapping of data findings.

Business applications learned in this course include competitor analysis, trend mining and many more.