Introduction to Text Mining
Course, bachelor, winter 2020, L.079.05501
General
Lectures
- Instructor. Henning Wachsmuth
- Location. Online
- Time. Thursday, 2pm – 5pm, c.t. (latest video upload, audio live chat)
- First date. October 29, 2020
- Last date. February 11, 2021
Tutorials
- Instructors. Milad Alshomary, Maximilian Spliethöver
- Location. Online
- Time. Wednesday, 2pm – 4pm, c.t. (latest video upload, audio live chat)
- First date. November 4, 2020
- Last date. February 10, 2021
Announcements
Description
This course teaches students all major skills needed to approach typical tasks in the analysis of natural language text. Starting from fundamentals of linguistics and statistics, the lecture gives an overview of several text analyses and covers a selection of them in detail. Both rule-based and statistical techniques are discussed, among the latter standard approaches from machine learning.
The students learn both theoretically and practically to design, implement, and evaluate text analysis algorithms for given tasks. Besides the topical content, the lecture aims to educate students in how to conduct scientific experiments and how to employ large datasets in experiments.
Lectures
The course will cover lectures on the following topics. The slides from each lecture will be put here, usually soon after the respective lecture has taken place. Slides marked with an asterisk (*) are not relevant for the exam. Notice that there may be updates of the slides (marked as such), so check from time to time.
- I. Overview (slides, videos)
- II. Basics of Linguistics (slides, videos)
- III. Text Mining using Rules (slides, videos)
- IV. Basics of Empirical Methods (slides, videos)
- V. Text Mining using Grammars (slides, videos)
- VI. Basics of Machine Learning (slides, videos)
- VII. Text Mining using Unsupervised Learning (slides, videos)
- VIII. Text Mining using Supervised Learning (slides, videos)
- IX. Practical Issues (slides, videos)
Slides with meta-information: