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732A47 Text Mining

Course information


Course sections

The three introductory modules are meant to give you the necessary background for the rest of the course.
You need to pass two out of the three introductory modules, and you are free to choose which module (if any) to skip.


Course literature
The following books will be used, in parts, during the course:

  • Natural Language Processing with Python.
    This book contains a lot of practical hands-on material using the NLTK toolkit for Python.
    The book's website is here, where the book can be read for free in HTML format. The publisher O'Reilly also sells the book in PDF format.
  • Foundations of Statistical Natural Language Processing.
    This book describes the background theory for computational linguistics and statistical analysis of text data.
    It available electronically for free here (for LiU students, but and probably also for students at most other Swedish universities).
    The book's website is here.
  • Extra material
Note: We will not order the books to the book stores on campus. Both books are available at all major internet book stores.


Course Introduction


Slides

Introduction to Python Programming



Recommended literature Slides Useful stuff Computer lab


Introduction to Statistical Modeling



Slides
Computer lab

Introduction to Computational Linguistics



Slides

Computer lab

Data models and Information Retrieval for Textual Data



Slides

Computer lab

Statistical Models for Textual Data



Slides
  • Slides - 1 per page | Slides - 4 per page
Computer lab


Text Mining Project



Slides

Computer lab


Page responsible: Mattias Villani
Last updated: 2013-04-04