CLT310: Information Retrieval and Search Engines - Spring 2017

Course Information

The course gives an overview of the basic principles and models used in information retrieval. The course includes lectures, practical assignments and project work to get started with existing tools and data resources. Students need to participate actively in the course and a good amount of self-studies is required.

Teacher: Jörg Tiedemann
Scope: 3 credits or 5 credits (including project)
WebOodi: CLT310


More details about the grading principles are given further below.

Preliminary Schedule

Time: Tuesdays 12-14
Place: U40 sali 19, Unioninkatu 40

17.01. Introduction and overview
24.01. Dictionaries and tolerant retrieval
  • Reading: [MRS] ch3
31.01. Ranked Retrieval and Evaluation
07.02. Efficient Scoring and Link Analyses
14.02. Web Search and Crawling
21.02. Guest Speaker: Dmitry Kan from AlphaSense and Insider Solutions: IR open state
  • Reading on QA Systems: [JM] ch28 [QA]
28.02. Seminar

Study materials and literature

Additional material may be added later.

Grading Principles

You will get points for the various assignments (lab assignments, seminar presentations, overview papers, project work and project reports). You can get 3 credits if you do the lab assignments and either present at the seminat or submit an overview paper on a selected topic. You can get a total of 5 credits if you work on an indivdual project and submit a project report in addition to the other assignments. The following points can be obtained by the different components:

lab assignments  15 points + 10 bonus points
seminar talk or overview paper  10 points
individual project  20 points

Points will be converted to grades with the following scales:

3 credits:  max 25p + 10p bonus
>24p = 5
21 - 24p = 4
17 - 20p = 3
13 - 16p = 2
9 - 12p = 1

5 credits:  max 45p + 10p bonus
>44p = 5
38 - 44p = 4
31 - 37p = 3
24 - 30p = 2
17 - 23p = 1

Links and Further Reading