Language Technology, 6 credits (TDP030)

Språkteknologi, 6 hp

Main field of study

Programming

Level

First cycle

Course type

Programme course

Examiner

Marco Kuhlmann

Director of studies or equivalent

Jalal Maleki

Available for exchange students

Yes
Course offered for Semester Period Timetable module Language Campus VOF
6KIPR Programming 6 (Spring 2018) 1 2 Swedish/English Linköping v

Main field of study

Programming

Course level

First cycle

Advancement level

G2X

Course offered for

  • Programming

Entry requirements

Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.

Prerequisites

  • discrete mathematics
  • programming

Previous courses in machine learning are useful but no requirement for the course.
 

Intended learning outcomes

Language technology is technology for the analysis and interpretation of natural language, a key component of smart search engines, personal digital assistants, and many other innovative applications. The goal of this course is to give an introduction to language technology as an application area, as well as to its basic methods. The course focuses on methods that process text.

On completion of the course, the student should be able to:

  1. explain basic methods for the analysis and interpretation of words, sentences, and texts
  2. practically apply language technology methods and systems to texts and text collections
  3. evaluate language technology components and systems using standard validation methods
  4. judge the difficulty and the feasibility of language technology applications

Course content

  • basic methods and techniques for the analysis and interpretation of words, sentences, and texts, such as text segmentation, part-of-speech tagging, syntactic analysis, semantic analysis, and text classification
  • language technology systems, such as information extraction systems and question answering systems
  • validation methods
  • tools, software libraries, and data

Teaching and working methods

The course is given in the form of lectures, lab sessions, and supervision in connection with a minor project. 

Examination

KTR1Optional written testsU, G0 credits
TEN1Written examinationU, 3, 4, 52 credits
LAB1Practical assignmentsU, 3, 4, 52 credits
UPG1Project assignmentsU, 3, 4, 52 credits


The optional written tests give bonus points for the first attempt at the written examination. The final grade for the course is the median of the grades awarded for LAB1, TEN1, and UPG1. 

Grades

Four-grade scale, LiU, U, 3, 4, 5

Department

Institutionen för datavetenskap

Director of Studies or equivalent

Jalal Maleki

Examiner

Marco Kuhlmann

Course website and other links

http://www.ida.liu.se/~TDP030/

Education components

Preliminary scheduled hours: 48 h
Recommended self-study hours: 112 h

Course literature

Kurskompendium som tillhandahålls av institutionen. / Lecture notes provided by the department.
Kurskompendium som tillhandahålls av institutionen. / Lecture notes provided by the department.
KTR1 Optional written tests U, G 0 credits
TEN1 Written examination U, 3, 4, 5 2 credits
LAB1 Practical assignments U, 3, 4, 5 2 credits
UPG1 Project assignments U, 3, 4, 5 2 credits


The optional written tests give bonus points for the first attempt at the written examination. The final grade for the course is the median of the grades awarded for LAB1, TEN1, and UPG1. 

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