Natural Language Processing

This module deals with computer processing of human languages, emphasizing a corpus-based empirical approach. The topics covered include: 1. Linguistic essentials. 2. Basic techniques and algorithms: Hidden Markov model, Viterbi algorithm, supervised learning algorithms. 3. Words: part-of-speech tagging. 4. Syntax: noun phrase chunking, named entity tagging, parsing (top down, bottom up, probabilistic). 5. Semantics: word sense disambiguation. 6. Pragmatics: discourse, co-reference resolution. 7. Applications: text categorisation, text summarisation, language identification, information extraction, question answering, machine translation.

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