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DD2477 Search Engines and Information Retrieval Systems 7.5 credits

Administer About course

The course discusses methods for indexing, ranking and searching in large document collections, as well as methods for evaluating different search models.

Information per course offering

Choose semester and course offering to see current information and more about the course, such as course syllabus, study period, and application information.

Termin

Information for Spring 2026 Start 13 Jan 2026 programme students

Course location

KTH Campus

Duration
13 Jan 2026 - 1 Jun 2026
Periods

Spring 2026: P4 (3 hp), P3 (4.5 hp)

Pace of study

25%

Application code

60251

Form of study

Normal Daytime

Language of instruction

English

Course memo
Course memo is not published
Number of places

Places are not limited

Target group
Open to all programmes from year 3 and for students admitted to a master's programme as long at is can be included in your programme.
Planned modular schedule
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Schedule
Schedule is not published

Contact

Examiner
No information inserted
Course coordinator
No information inserted
Teachers
No information inserted

Course syllabus as PDF

Please note: all information from the Course syllabus is available on this page in an accessible format.

Course syllabus DD2477 (Autumn 2025–)
Headings with content from the Course syllabus DD2477 (Autumn 2025–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Basic and advanced technologies for information retrieval, indexing and ranking; 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

After passing the course, the student shall be able to

  • explain and use concepts in information retrieval such as indexing, ranking, boolean search model, vector space model
  • implement methods for indexing, search, and ranking of a very large number of documents with hyperlinks
  • use tools and software libraries for information retrieval
  • be able to evaluate algorithms and systems for information retrieval

in order to be able to

  • work for companies that specialise in information retrieval
  • carry out a master's degree project in computer science with a specialisation in information retrieval
  • be an important link between systems designers, programmers, and interaction designers in industry as well as in research projects.

Literature and preparations

Specific prerequisites

Knowledge and skills in programming, 6 credits, equivalent to completed course DD1310-DD1319/DD1331/DD1333/DD1337/DD1321/DD100N/ID1018.

Knowledge of algorithms and data structures, 6 credits, equivalent to completed course DD1320-DD1328/DD1338/ID1020/ID1021.

Knowledge of linear algebra, 7.5 credits, equivalent to completed course SF1624/SF1684/SF1672.

Literature

You can find information about course literature either in the course memo for the course offering or in the course room in Canvas.

Examination and completion

Grading scale

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

Examination

  • LAB1 - Computer assignments, 4.5 credits, grading scale: A, B, C, D, E, FX, F
  • PRO1 - Project assignment, 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.

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

Examiner

Profile picture Johan Boye

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

EECS/Intelligent Systems

Main field of study

Computer Science and Engineering

Education cycle

Second cycle

Supplementary information

In this course, the EECS code of honor applies, see:
http://www.kth.se/en/eecs/utbildning/hederskodex

DD2477 is replacing and overlapping DD2476 and therefore cannot be combined with that course.