- Sep 22 Assignment 2 has been announced. The Jupyter notebook you need to complete can be found in your personal GitHub repository. This assignment is wort 10 points. The deadline is Oct 6, 16:00.
- Sep 21 You may use the Issues tab for posting questions. That way other could also benefit from a clarification. That way other could also benefit from a clarification (and you can also help your fellow students). For example, multiple people raised the issue of "infected" files for A1.3, which has now been clarified there.
- Sep 21 New format for the next 4 weeks! As of this week, Mondays will be lectures exclusively (lecture videos will follow). The exercises will be posted and done on Tuesdays. People can join in person in the lecture room or work on them remotely and ask for help on the dedicated slack channel. (Note: this slack channel is reserved for this time-slot, i.e., Tuesdays between 14.15 and 16.00).
- Sep 21 Results for assignments A1.1 and A1.2 have been posted on Canvas. If you have any questions, you can ask them during the Wednesday labs or send an email to [email protected].
DISCLAIMER: Everything is subject to change.
The course follows a hybrid format, where lecture videos are provided online and classroom time is used for discussion, exercises, and working on assignments.
This course involves self-study (which can be completed online): You're expected to watch the lecture videos, read the corresponding book chapters/sections listed on the last slide of each lecture deck, as well as complete the exercises on GitHub.
There is also a physical component which is not obligatory, but highly recommended for an optimal learning experience. This involves discussion and exercises in a regular classroom setting.
There is a double lecture on Mondays, 14:15-16:00 (without dividing into A/B groups). The Tuesday 14:15-16:00 slot is kept for open office hours (in KE E-433). Note that open office hours are meant for questions regarding the lecture material and/or exercises. Issues related to the assignments should be addressed at lab sessions on Wednesdays.
The semester is divided into lecture and group project work periods, with an (optional) trial exam in between.
- Mondays and Tuesdays are classes for discussion and exercises, led by Krisztian Balog (KB).
- The respective video lectures are made available either before or after the class (depending on the topic). If the video is made available before the class, you are expected to watch it, in order to be able to meaningfully participate in the discussion and undertake the exercises.
- Wednesdays are labs for getting help on the obligatory assignments, led by Trond Linjordet (TL).
- Assignments are to be solved individually. They constitute 50% the project work.
A trial exam will be made available mirroring the same setup that will be used at the final exam. The exam will not be corrected, but the answer key will be shared.
Students will need to complete a project in groups of 2-3, and write a report that will be graded.
There will be a pool of options to select a project from. During the project period, each group can request a 15mins dedicated weekly discussion slot with the lecturer during the class hours (Mon/Tue), and can get feedback on the draft report from the teaching assistant during lab hours (Wed). Both in-person and remote (Zoom) options will be available.
| Date | Topic | Lectures | Exercises |
|---|---|---|---|
| Aug 24 | L1: Welcome and introduction | slides | exercises, solutions |
| Aug 25 | L2: Text classification | slides | exercises, solutions |
| Aug 31 | L3: Text preprocessing | video lecture, slides | exercises, solutions |
| Sep 1 | L4: Text classification evaluation | video lecture, slides | exercises, solutions |
| Sep 7 | L5: Text classification: Naive Bayes | slides | exercises |
| L6: Text clustering | (slides to be added) | exercises | |
| Sep 21 | L6: Search engine architecture | slides | exercises, solutions |
| L7: Indexing and query processing | slides | ||
| L8: Retrieval evaluation | slides | ||
| Sep 28 | L9: Retrieval models | ||
| L10: Query modeling | |||
| L11: Web search | |||
| Oct 5 | L12: Semantic search: Entity-oriented search | ||
| L13: Semantic search: Entity retrieval | |||
| L14: Semantic search: Entity linking | |||
| Oct 12 | L15: Learning to rank | ||
| L16: Neural IR (invited) | |||
| L17: Table retrieval (invited) |
The overall grade comes from two components:
- Project work (40%), of which
- 50% individual assignments
- 50% group project
- Written exam (60%)
Note that the project grade needs to be >F in order to pass the course.
- For all course-related matters, the primary contact email is [email protected]
- Wednesday labs are for working on the assignments. This is the time to get help!
- If you need to talk to the lecturer, make an appointment via email. No drop-ins unannounced!