DD2476 Search Engines and Information Retrieval Systems 9.0 credits
This course will be discontinued.
Last planned examination: Spring 2024
Decision to discontinue this course:
The course is discontinued at the expiration of spring term 2024 in accordance with Head of School decision:: J-2022-0856.
Decision date: 07/06/2022
The course was given for the last time during the spring semester 2021. Final opportunity for examination in the course will be given spring term 2024.
The assessment modules LABA on 6 higher education credits and lab on 3 higher education credits can up to the spring semester 2024 be examined after contact with the examiner. Students are offered no teaching.
A course in computer science focusing on basic theory, models, and methods for information retrieval.
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.
Course disposition
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.
Equipment
Literature
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
Grading scale
Examination
- 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
Opportunity to raise an approved grade via renewed examination
Examiner
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 web
Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.
Course web DD2476Offered by
Main field of study
Education cycle
Add-on studies
Contact
Supplementary information
In this course, the EECS code of honor applies, see:
http://www.kth.se/en/eecs/utbildning/hederskodex
The course is replaced by DD2477 from 2022.