Text analysis

Some books

  1. Murugan Anandarajan, Chelsey Hill, Thomas Nolan: Practical Text Analytics. Springer 2019.
  2. Ashish Kumar, Avinash Paul: Mastering Text Mining with R. Packt 2016. lemmatization - page 63
  3. Benjamin Bengfort, Rebecca Bilbro, and Tony Ojeda: Applied Text Analysis with Python. O’Reilly 2018.
  4. Michael W. Berry, Jacob Kogan: Text Mining - Applications and Theory. Wiley 2010.
  5. Stefan Th. Gries: Quantitative Corpus Linguistics with R - A Practical Introduction. Second Edition, Routledge 2017.
  6. Daniel Jurafsky, James H. Martin: Speech and Language Processing - An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition.Third Edition draft, Stanford 2020. PDF
  7. Matthew L. Jockers, Rosamond Thalken: Text Analysis with R - For Students of Literature. Second Edition, Springer 2020.
  8. Akshay Kulkarni, Adarsha Shivananda: Natural Language Processing Recipes. Apress 2019.
  9. Ted Kwartler: Text Mining in Practice with R. Wiley 2017.
  10. Rada Mihalcea, Dragomir Radev: Graph-based natural language processing and information retrieval. CUP 2011.
  11. Jacob Perkins: Python 3 Text Processing with NLTK 3 Cookbook. Packt 2014.
  12. Julia Silge, David Robinson: Text Mining with R - A Tidy Approach. O’Reilly 2018.
  13. Taylor Arnold, Lauren Tilton: Humanities Data in R. Springer 2015.
  14. Ani Nenkova and Kathleen McKeown: A Survey of Text Summarization Techniques. in Charu C. Aggarwal, ChengXiang Zhai: Mining Text Data. Springer 2012.
ru/hse/ta.txt · Last modified: 2021/12/03 06:24 by vlado
 
Except where otherwise noted, content on this wiki is licensed under the following license: CC Attribution-Noncommercial-Share Alike 3.0 Unported
Recent changes RSS feed Donate Powered by PHP Valid XHTML 1.0 Valid CSS Driven by DokuWiki