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Course: Natural Language Processing
The main objective of this course is to introduce the students to the underlying problems when facing with natural languages data.
Practical exercises will complete the theoretical presentation.
Introduction to Perl and XML; Introduction to linguistics (morphology, syntax, semantics); simple statistical approaches (KWIC, concordances); automata and natural language (FSTN, RTN, ATN); Spelling detection and correction; Statistical models (counting words, bigramns, entropy); Markov chains; Hidden Markov chains; Information retrieval.
The final mark is based on both a final written exam and the results of the practical exercices.
Advances NLP tools
To get a version of Prolog and Corpora