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Natural Language Processing

Code 11535
Year 1
Semester S2
ECTS Credits 6
Workload PL(30H)/T(30H)
Scientific area Informatics
Mode of delivery Face to face.
Work placements Not aplicable.
Learning outcomes Study of the main fundamental subjects from Human Language Technology, with a special focus on written language. Analysis of a number of theoretical principles and and practical techniques involved in human language processing. At the end of the course the student should know the main themes of the Human Language Technology, especially in terms of written language. This includes the acquisition of theoretical knowledge of Natural Language Processing and its fundamental principles, at a morphological, syntactical, semantic, and pragmatic levels. The student should also gain mastery with several tools and technologies within those areas, which were being experienced through a number of exercises and assignments, implemented in laboratory.
Syllabus Part I - Foundations
1. Classical Introduction
2. Empirical Introduction

Part II - Theories
3. Modeling Language
4. Polilexical Units
5. Segmentation into Topics
6. Lexical Chains

Part III - Applications
7. Information Retrieval
8. Information Extraction
9. Text Classification and Clustering
10.Automatic Summarization
Main Bibliography Main Bibliography

Jurafsky et al, Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition, Prentice Hall, 2000, ISBN: 0130950696


Secondary Bibliography

R. Mitkov, The Oxford Handbook of Computational Linguistics, Oxford University Press, 2003, ISBN: 0-19-823882-7

C.D. Manning & H. Schütze, Foundations of Statistical Natural Language Processing, MIT Press, 1999, ISBN: 0262133601

R. Dale et al., Handbook of Natural Language Processing, Dekker, 2000, ISBN:0-8247-9000-6

M. Crochemore & W. Rytter, Jewels of Stringology, World Scientific Pub Co, 2002, ISBN: 9810247826
Planned learning activities and teaching methods In the theoretical classes, concepts are exposed, explained and exemplified, as well as possible. In the practical classes students computationally implement the learnt theoretical knowledge. A number of exercises in Java programming language are prepared and followed.
Metodologias de Ensino e Critérios de Avaliação A avaliação compreenderá uma componente escrita, na forma de duas frequências (F1 e F2). Um trabalho escrito (TE) de revisão de um tópico relevante da PLN e um trabalho prático (TP) de aplicação de conhecimentos adquiridos.

Assim, a classificação por frequência (CF) é calculada ponderando as classificações obtidas nas quatro componentes listadas anteriormente:

CF = 25% F1 + 25% F2 + 20% TE + 30% TP.

No caso de CF < 6 valores o aluno ficará não admitido a exame, reprovando à unidade curricular. Se CF = 9.5 o aluno dispensa a realização de exame. Caso vá a exame contará sempre a melhor classificação final. A classificação em exame (CE) é calculada da seguinte forma:

CF = 50% Exame + 20% TE + 30% TP.

A assiduidade mínima requerida é de 50% nas aulas teóricas e 50% nas práticas.
Language Portuguese. Tutorial support is available in English.
Last updated on: 2016-11-16

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