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521158S Natural Language Processing and Text Mining, 5 ECTS cr 
Code 521158S  Validity 01.08.2017 -
Name Natural Language Processing and Text Mining  Abbreviation NatLaPrcTxMi 
Scope5 ECTS cr   
TypeAdvanced Studies Discipline4307 Information Engineering 
TypeCourse   
  Grading1 - 5, pass, fail 
 
   
Unit Computer Science and Engineering DP 

Teachers
Name
Mourad Oussalah 

Description
ECTS Credits 

5 ECTS credits / 120 hours of works

 
Language of instruction 

English

 
Timing 

Period 1. It is recommended to complete the course at the end of period 1

 
Learning outcomes 

Upon completing the course, the student is expected to i) comprehend, design and implement basic (online) text retrieval and query systems; ii) account for linguistic aspects and perform word sense disambiguation; iii) perform basic (statistical) inferences using corpus; iv) manipulate (statistical) language modelling toolkits, online lexical databases and various natural language processing tools.

 
Contents 

Foundation of text retrieval systems, Lexical ontologies, word sense disambiguation, Text categorization, Corpus-based inferences and Natural Language Processing tools

 
Mode of delivery 

Face- to-face teaching and laboratory sessions

 
Learning activities and teaching methods 

Lectures (24 h), tutorial/laboratory sessions (16h), seminar (6h) and practical work. The course is passed with an approved practical work and class test. The implementation is fully in English.

 
Target group 

students with (moderate to advanced) programming skills in Python

 
Prerequisites and co-requisites 

Programming skills (preferably) in Python

 
Recommended optional programme components 

The course is an independent entity and does not require additional studies carried out at the same time

 
Recommended or required reading 

Introduction to Information Retrieval, by C. Manning, P. Raghavan, and H. Schütze. Cambridge University Press, 2008. (Free from http://nlp.stanford.edu/IR-book/) Foundations of statistical natural language processing, by Manning, Christopher D., Schütze, Hinrich. Cambridge, Mass.: MIT Press, 2000

 
Assessment methods and criteria 

One class test (30%) in the middle of the term + Project work (70%)

Read more about assessment criteria at the University of Oulu webpage.

 
Grading 

1-5

 
Person responsible 

Mourad Oussalah

 
Working life cooperation 

-

 


Current and future instruction
Functions Name Type ECTS cr Teacher Schedule
Registration Natural Language Processing and Text Mining  Course  Mourad Oussalah  31.08.20 -22.10.20

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