HIOK03597U Language Processing II
Volume 2016/2017
Education
IT and Cognition
Content
Have you ever wondered how to build a system that can process text automatically, for example translate between languages, reveal syntactic structure, or extract semantic information?
In this class we will explore fundamental algorithms and models for natural language processing, and describe the application of these algorithms and models to key problems in natural language processing, such as POS tagging, syntactic, semantic and discourse analysis, and machine translation.
The main focus will be on the practical implementation of methods for syntactic parsing.
The format of the class consists of lectures (including guest lectures), student presentations, and project work.
Teaching and learning methods
Lectures
Workload
- Category
- Hours
- Class Instruction
- 42
- Course Preparation
- 105
- Exam Preparation
- 59
- Total
- 206
Sign up
Self Service at
KUnet
Exam
- Credit
- 7,5 ECTS
- Type of assessment
- Written examinationWritten take-home assignment, set subject
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Course information
- Language
- English
- Course code
- HIOK03597U
- Credit
- 7,5 ECTS
- Level
- Full Degree MasterPart Time Master
- Duration
- 1 semester
- Placement
- Spring
- Schedule
- C1
- Study board
- Study Board of Department of Nordic Research
Contracting department
- Department of Scandinavian Studies and Linguistics
Course responsibles
- Jürgen Wedekind (9-6d7a6867686e6c7167436b7870316e7831676e)
- Peter Juel Henrichsen (7-726c6a306b64654265647530666d)
Lecturers
Jürgen Wedekind and Peter Juel Henrichsen
Saved on the
27-01-2017