INF5830 – Natural language processing
Schedule, syllabus and examination date
Methods and algorithms for natural language processing with an emphasis on large text collections. The methods will be symbolic, statistical and hybrid with the use of machine learning techniques. This will be applied to tasks like collocations, tagging, sense disambiguation, probabilistic analysis.
After completing INF5830
- You can set up and implement language technology experiment step by step
- You can evaluate language technology components
- You for a given language technological problem consider which computer programs will be suitable, install them and apply them to linguistic data.
- You are familiar with a sample of machine learning techniques and can assess which ones are suitable for a given problem
- You can explain the interaction between rule based and probabilistic methods in language technology.
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Recommended previous knowledge
Some knowledge in statistics is an advantage.
2 hours of lectures and two hours of group work per week. Mandatory assignments must be completed during the course. Rules for mandatory assignments.
A 4 hour written exam. The mandatory assignments must be approved prior to the exam.
Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.
Explanations and appeals
Resit an examination
Students who can document a valid reason for absence from the regular examination are offered a postponed examination at the beginning of the next semester.
Re-scheduled examinations are not offered to students who withdraw during, or did not pass the original examination.
Withdrawal from an examination
It is possible to take the exam up to 3 times. If you withdraw from the exam after the deadline or during the exam, this will be counted as an examination attempt.
It is strongly recommended to attend the first lecture since it will be given important information.