DD2475 Information Retrieval 9.0 credits
This course has been cancelled.
A course in computer science focusing on basic theory, models, and methods for information retrieval.
Education cycleSecond cycle
Main field of studyComputer Science and Engineering
Grading scaleA, B, C, D, E, FX, F
Last planned examination: autumn 13.
At present this course is not scheduled to be offered.
Intended learning outcomes
After completing the course you will be able to:
- Explain the concepts of indexing, vocabulary, normalization and dictionary in Information Retrieval
- Define a boolean model and a vector space model, and explain the differences between them
- Explain the differences between classification and clustering
- Discuss the differences between different classification and clustering methods
- Choose a suitable classification or clustering method depending on the problem constraints at hand
- Implement classification in a boolean model and a vector space model
- Implement a basic clustering method
- Give account of a basic spectral method
- Evaluate information retrieval algorithms, and give an account of the difficulties of evaluation
- Explain the basics of XML and Web search.
Course main content
Basic and advanced techniques for information systems: information extraction; efficient text indexing; indexing of non-text data; Boolean and vector space retrieval models; evaluation and interface issues; XML, structure of Web search engines; clustering, classification; spectral methods, random indexing; data mining.
Single course students: 90 university credits including 45 university credits in Mathematics or Information Technology. English B, or equivalent.
A level in Mathematics corresponding to at least 30 credits, including courses in Linear Algebra, Calculus in one and several variables, Mathematical Statistics, and a level in Computer Science corresponding to at least 15 credits. It is also beneficial to have taken courses in Machine Learning, Artificial intelligence, Language Engineering and/or Database Technology.
C. D. Manning, P. Raghavan and H. Schütze: Introduction to Information Retrieval, Cambridge University Press, 2008.
- LAB1 - Laboratory Works, 3.0, grading scale: P, F
- LAB2 - Project, 3.0, grading scale: A, B, C, D, E, FX, F
- TEN1 - Exam, 3.0, grading scale: A, B, C, D, E, FX, F
In this course all the regulations of the code of honor at the School of Computer science and Communication apply, see: http://www.kth.se/csc/student/hederskodex/1.17237?l=en_UK.
Requirements for final grade
The students participating in the course are expected to take part in all activities in the course with a particular emphasis on the exercises and laboratories. In addition the course focuses on training:
* independently acquiring knowledge
* oral and written presentation
Examination by one written exam (TEN1; 3.0 credits), laboratory assignments (LAB1; 3.0 credits), and a project assigment assessed orally and in writing (LAB2; 3.0 credits).
Hedvig Kjellström <email@example.com>
This course is replaced by DD2476 Search Engines and Information Retrieval Systems from the year 11/12.
Course syllabus valid from: Autumn 2010.
Examination information valid from: Autumn 2010.