Language technology resources
Summary
The purpose of this course is to give a further introduction to algorithmic resources for language technology.
About
The purpose of this course is to give a further introduction to algorithmic resources for language technology such as algorithms for word sense induction and disambiguation, learning algorithm and classification of sentences. Language technology resources, such as corpora, lexicons, syntax and text as well as language models will be discussed in connection with relevant algorithms.
Prerequisites and selection
Entry requirements
Admission to the course requires having passed the following courses:
- LT2001 Introduction to programming 7.5 credits
- LT2002 Introduction to formal linguistics 7.5 credits
- LT2003 Natural language processing, 15 credits (or LT2123 Basic skills for language technology, 7.5 credits together with LT2124 Themes in NLP and language technology, 7.5 credits)
- LT2212 Statistical methods 7.5 credits (or LT2222 Machine learning for statistical NLP: introduction 7.5 credits)
or equivalent language technology competence.
English 6 or equivalent is also required.
Selection
Selection is based upon the number of credits from previous university studies, maximum 165 credits.
