Interactive Multi-Criteria Ranking

Rankings of items enable users to a) select a top candidate item, b) focus on a small set of highly preferable items or c) identify items that are ranked particularly weak.

The human-centered ranking of multi-dimensional items is a non-trivial task. Comparing complex items to each other in order to create a ranking can be time-consuming and especially if data sets are large, there is no guarantee that the result is satisfying. A shift from item granularity to attribute granularity might be beneficial to address complex decision-making problems. As such, we assume that enabling users to define item characteristics (attributes) can be most useful. The question is: how can preferences of users be matched best?

In this project, we characterize, design, and evaluate an interactive visual tool consisting of a server and a web interface to support attribute-based item ranking. The main idea of the project is to implement a tool that allows users to express their attribute preferences for flats to find the best matching flat for their needs and constraints. The tool should allow users to express their preferences in a visual-interactive way. Based on those preferences the tool should calculate a ranking of items and present the result to the user.

In short, the project consists of the following:

• A literature review of existing approaches for multi-criteria decision making
• The design, implementation, and evaluation of a tool that supports users in finding a flat to rent based on their attribute preferences
• A (small) written report that elaborates on the findings of the literature review, describes the implemented tool and the chosen approaches, and outlines possible areas for future work

The project will be supervised by Jenny Schmid and Prof. Jürgen Bernard. Ideally, the project should start at the end of April 2022 and the duration of the project will be approximately 9 months. A group of 3-5 students will be working on the project.

The project language is English, therefore, you are required to have good English knowledge (written and oral).

The programming languages of the project are not yet defined and are up for discussion by the project team (preferably Python or Java for the back end and JavaScript for the front end). The code will be versioned through GitLab and the tool will be hosted on the IFI server.

If possible (depending on the COVID situation), regular meetings will be held on-site.

The ultimate goal of the project would be to submit a paper at the end of 2022, therefore students with a research interest are preferred.

You should have the following skills for this project:

• Profound programming skills (preferably with Python, Java and/or JavaScript), ideally with a full-stack background
• Basic knowledge of databases (e.g. how to write a database statement to retrieve data)
• Experience in working with version control systems (e.g. Git, we will be using GitLab)
• Interest in research

In addition, it would be nice if you have experience in one of the following areas (but it is not a must):

• UI / UX design
• Testing (e.g. Unit Testing)
• DevOps such as CI/CD and application deployment
• REST or any other framework that supports the communication between the back and front end
• CSS and HTML
• Front end frameworks such as ReactJS, Angular, Material Design, Bootstrap, etc.
• Back end frameworks such as Django, Flask, Spring, etc.

The topic will be assigned through the "Master Project Market" in Spring 2022. Watch out for the event so that you don't miss it!

Interested students should send their complete application to Prof. Jürgen Bernard.

Applications should include:

• A short, informal letter of motivation including your expectation for the project, the skills you want to learn, and your experience with data visualizations (if any)
• Your CV
• Your transcript of records from your Master's and Bachelor's Degree

If you have any questions about the project, please feel free to contact  Prof. Jürgen Bernard or Jenny Schmid.