392285 ISY Project: Unravelling the canteen menu generation through data mining (Pj) (SoSe 2023)

Contents, comment

Have you ever wondered why they serve noodles as side dish for spaghetti in the canteen of Bielefeld University? Or have you longed for a splendid bowl of swedish apple creme just to find out that they are simply not offering any? Fear no more. Over the past 8 months, we have scraped the website of the Studierendenwerk to gather the weekly canteen plan. This raw information will build the data set that this project aims to analyze more closely. The idea is to execute the typical pipeline of data selection, preprocessing, transformation, mining and interpretation to uncover hidden patterns in a scientifically sound and structured way on a real world data set with all of its flaws, errors and missing fields. The results of the project will be summarized in a written report whose length depends on the group size. Will saithe from Alaska play a larger role than we all anticipate? At the current point in time, we simply don't know. But we are eager to find out. Possible research questions for this project include:
- Which (family of) algorithms works best to predict main dish X?
- Can you find meaningful clusters of dishes appearing at the same time and how do they relate to each other?
- How consistent is the canteen plan to itself? Are there any regularities like predictable repetitions?

In case the proposal would not attract enough students for a team project, it can be adapted into an individual project or a project for two students (tandem project).

Teaching staff

Dates ( Calendar view )

Frequency Weekday Time Format / Place Period  

Show passed dates >>

Subject assignments

Module Course Requirements  
39-M-Inf-GP Grundlagenprojekt Intelligente Systeme Gruppenprojekt Ungraded examination
Student information

The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.


Required skills:
Basic data mining knowledge

No eLearning offering available
Address:
SS2023_392285@ekvv.uni-bielefeld.de
This address can be used by teaching staff, their secretary's offices as well as the individuals in charge of course data maintenance to send emails to the course participants. IMPORTANT: All sent emails must be activated. Wait for the activation email and follow the instructions given there.
If the reference number is used for several courses in the course of the semester, use the following alternative address to reach the participants of exactly this: VST_403525048@ekvv.uni-bielefeld.de
Notes:
Additional notes on the electronic mailing lists
Last update basic details/teaching staff:
Wednesday, February 8, 2023 
Last update times:
Monday, February 6, 2023 
Last update rooms:
Monday, February 6, 2023 
Type(s) / SWS (hours per week per semester)
project (Pj) / 2
Department
Faculty of Technology
Questions or corrections?
Questions or correction requests for this course?
Planning support
Clashing dates for this course
Links to this course
If you want to set links to this course page, please use one of the following links. Do not use the link shown in your browser!
The following link includes the course ID and is always unique:
https://ekvv.uni-bielefeld.de/kvv_publ/publ/vd?id=403525048
Send page to mobile
Click to open QR code
Scan QR code: Enlarge QR code
ID
403525048