Natural language processing

lfial2620  2017-2018  Louvain-la-Neuve

Natural language processing
5 credits
22.5 h
Q1
Teacher(s)
Fairon Cédrick;
Language
French
Prerequisites
/
Main themes
The course begins with the architectural study of a complex automatic language processing system (recognition, analysis, generation). It continues with the study of the central linguistic theories and computer formalities of ANLP. Special attention is given to the presentation and analysis of real applications.
Aims

At the end of this learning unit, the student is able to :

1

The course will teach students the basic theory necessary to understanding the current objectives and issues of the automatic natural language processing (ANPL). At the same time, students will learn to analyse and explain the practical and technical limits that arise in the elaboration of computer systems aimed at language processing (problems of ambiguity, necessity of linguistic resource adaptability, multilingualism, etc.). By the end of the course, students will have received an overview of the "state of the art" in ANLP, be able to take a critical approach to ANLP applications, and have a general knowledge of the main theories in the field.

 

The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Content
The course is comprised of interactive lectures. A reading folder made up of specialised articles allows students to prepare for courses, which begin with a question and answer period.
Teaching methods
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Evaluation methods
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Other information
Nil.
Online resources
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Bibliography
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Faculty or entity
FIAL


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Linguistics

Master [120] in French and Romance Languages and Literatures : French as a Foreign Language

Master [120] in Ancient and Modern Languages and Literatures

Master [120] in data Science: Statistic