Foundations of Language Technology

Organization

  • Lecture: Thursday 09:50-11:30, Room S202/C205
  • Practice class: Monday 11:40-13:20, Room S202/C120

The learning material is available from the Moodle eLeaning platform.
The required passcode will be distributed during the lecture.

The first lecture will be on October 19 and the first meeting of the practice class is scheduled for October 23, 2017.

Exam

  • Date/Time: Friday, 02.03.2018, 09:00–11:00
  • Room: Announced via Moodle

Teaching Staff

We currently do not have fixed office hours, so please contact us by mail to get an appointment.

Course Content

The lecture offers an introduction into the perspectives, problems, methods and techniques of text technology. All examples and tutorials are based on the programming language Python.

Key topics:

  • Natural language processing (NLP)

    • Tokenization and segmentation
    • Part-of-Speech tagging
    • Creating and using text corpora
    • Statistical analysis
    • Syntactic analysis

  • Machine Learning

    • Categorization and classification
    • Information extraction

  • Introduction to Python

    • Structured programming
    • Data structures and IO
    • NLTK library for NLP
    • Usage of further libraries such as scikit-learn

The course is based on the Python programming language together with an open source library called the Natural Language Toolkit (NLTK). NLTK allows explorative and problem-solving learning of theoretical concepts without the requirement of extensive programming knowledge.

The course assumes familiarity with basic computing concepts, but will not assume any knowledge of the Python language, which will be acquired during the course. If you like to work with your own notebook, we kindly ask you to follow the installation instructions given at http://www.nltk.org/download.

Literature

Steven Bird, Ewan Klein, Edward Loper: Natural Language Processing with Python, O'Reilly, 2009. ISBN: 978-0596516499. [the free online version is slightly newer than the printed book as it is being prepared for a second edition]

Expectations

What you can expect from us:

  • problem-based and explorative learning
  • stimulating environment
  • interactive lecture

What we expect from you:

  • commitment
  • feedback
  • active participation

If you like to have a jump start on NLTK, have a look at this video.

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