Coursebooks 2016-2017

PDF
 

Introduction to natural language processing

CS-431

Lecturer(s) :

Chappelier Jean-Cédric
Rajman Martin

Language:

English

Summary

The objective of this course is to present the main models, formalisms and algorithms necessary for the development of applications in the field of natural language information processing. The concepts introduced during the lectures will be applied during practical sessions.

Content

Several models and algorithms for automated textual data processing will be described: (1) morpho-lexical level: electronic lexica, spelling checkers, ...; (2) syntactic level: regular, context-free, stochastic grammars, parsing algorithms, ...; (3) semantic level: models and formalisms for the representation of meaning, ...

Several application domains will be presented: Linguistic engineering, Information Retrieval, Text mining (automated knowledge extraction), Textual Data Analysis (automated document classification, visualization of textual data).

Keywords

Natural Language Processing; Computationnal Linguisitics; Part-of-Speech tagging; Parsing

 

Learning Outcomes

By the end of the course, the student must be able to:

Teaching methods

Ex cathedra ; practical work on computer

Expected student activities

attend lectures and practical sessions, answer quizzes.

Assessment methods

4 quiz during semester 25%, final exam 75%

Supervision

Office hours No
Assistants No
Forum No

Resources

Bibliography

  1. M. Rajman editor, "Speech and Language Engineering", EPFL Press, 2006.
  2. Daniel Jurafsky and James H, Martin, "Speech and Language Processing", Prentice Hall, 2008 (2nd edition)
  3. Christopher D. Manning and Hinrich Schütze, "Foundations of Statistical Natural Language Processing", MIT Press, 2000
  4. Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval, Cambridge University Press. 2008
  5. Nitin Indurkhya and Fred J. Damerau editors, "Handbook of Natural Language Processing", CRC Press, 2010 (2nd edition)

Ressources en bibliothèque
Websites

In the programs

  • Digital Humanities, 2016-2017, Master semester 2
    • Semester
       Spring
    • Exam form
       Written
    • Credits
      4
    • Subject examined
      Introduction to natural language processing
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      2 Hour(s) per week x 14 weeks
    • Exercises
      2 Hour(s) per week x 14 weeks
    • Semester
       Spring
    • Exam form
       Written
    • Credits
      4
    • Subject examined
      Introduction to natural language processing
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      2 Hour(s) per week x 14 weeks
    • Semester
       Spring
    • Exam form
       Written
    • Credits
      4
    • Subject examined
      Introduction to natural language processing
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      2 Hour(s) per week x 14 weeks
    • Semester
       Spring
    • Exam form
       Written
    • Credits
      4
    • Subject examined
      Introduction to natural language processing
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      2 Hour(s) per week x 14 weeks

Reference week

 MoTuWeThFr
8-9     
9-10     
10-11     
11-12     
12-13     
13-14   INM200 
14-15    
15-16   INF1
INM200
 
16-17    
17-18     
18-19     
19-20     
20-21     
21-22     
 
      Lecture
      Exercise, TP
      Project, other

legend

  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German