Selected Topics in Natural language Processing

Course Description

Fundamentals of natural language processing. Computational morphology. Formal syntax: unification grammars, statistical parsing, dependency parsing. Computational semantics: formal semantics, distributional semantics, semantic role labeling, textual entailment. Discourse analysis: rhetorical parsing, coreference resolution. Machine learning for natural language processing: sequence labeling, probabilistic generative models, discriminative methods, semisupervised learning. Language technologies and resources. Applications in machine translation, text mining, information retrieval and extraction.

Study Programmes

Postgraduate doctoral study programme


Christopher D. Manning, Hinrich Schütze (1999.), Foundations of Statistical Natural Language Processing, MIT Press
Ruslan Mitkov (Ed.) (2005.), The Oxford Handbook of Computational Linguistics, Oxford University Press
Steven Abney (2007.), Semisupervised Learning for Computational Linguistics, CRC Press

For students


ID 154846
  Winter semester
L2 English Level