Vorlesung mit Übung: Computerlinguistik, M.Sc.Leitung: Stefan Thater, Clayton Greenberg
Ort: Geb. C72, Konferenzraum 2.11
Zeit: Tue 8-10, Thu 8-10
Geeignet für: M.Sc.
The goal of the course is to introduce the students to various standard algorithms in computational linguistics. The focus is on the structure of the algorithms, i.e. their data structures and mechanisms.
The course discusses standard algorithms used for various types of linguistic processing in computational linguistics. The algorithms discussed in the course range from shallow methods such as pattern matching algorithms for strings and trees, and finite state methods; to machine learning and statistical techniques such as Hidden Markov Models and decision trees; to various algorithms used in deep linguistic processing. Examples of the latter are memoization techniques, unification, graph algorithms, and inferencing with ontologies. The algorithms are illustrated with practical applications from computational linguistics. The students will gain hands-on experience with the algorithms either through using existing implementations or by having to implement provided exercises.
There will be exercises and a written exam at the end of the semester.
D. Jurafsky and J. H. Martin: Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, Prentice-Hall, 2000.
C. Manning and H. Schütze: Foundations of Statistical Natural Language Processing, MIT Press, 1999.
Additional readings will be provided during the semester.
Stellung im Studienplan
Core Course, Area CL ( Computational Linguistics)
Standard time slot 2nd semester.
Required course for M.Sc. with specializations CL and LT.