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DD2476 Search Engines and Information Retrieval Systems 9.0 credits

A course in computer science focusing on basic theory, models, and methods for information retrieval.

Course offerings are missing for current or upcoming semesters.
Headings with content from the Course syllabus DD2476 (Spring 2022–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Basic and advanced technologies for information retrieval: information extraction; efficient text indexing; indexing of non-textual data; boolean models and vector space models for search; evaluation and user interface issues; the structure of Internet search engines.

Intended learning outcomes

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

* explain the concepts indexing, vocabulary, normalisation and dictionary in information retrieval,

* give an account of different distance measures for text and choose a distance measure that is appropriate for a given problem,

* define a boolean model and a vector space model and explain the difference between them,

* implement a method for ranked search of a very large number of documents with hyper links,

* evaluate information retrieval algorithms and give an account of difficulties with evaluation,

* give an account of the structure of an Internet search engine.

Literature and preparations

Specific prerequisites

SF1604 Linear Algebra, SF1901 Basic Statistics and Probability Theory, DD1338 Algorithms and Data Structures or equivalent courses.

Recommended prerequisites

A level in Mathematics corresponding to at least 30 credits, including courses in Linear Algebra and Mathematical Statistics, and a level in Computer Science corresponding to at least 15 credits.


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Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F


  • LABA - Laboratory lessons, 6.0 credits, grading scale: A, B, C, D, E, FX, F
  • LABB - Laboratory lessons, 3.0 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Opportunity to complete the requirements via supplementary examination

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Opportunity to raise an approved grade via renewed examination

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Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

Computer Science and Engineering

Education cycle

Second cycle

Add-on studies

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Johan Boye, e-post: