The mission of the Knowledge Discovery group is to extract the maximum value out of data. To that end, we follow a data-driven approach, which is domain-agnostic in its application. Our research is related to the scientific fields of machine learning and natural language processing. Methods from these fields form the algorithmic base of data science, artificial intelligence and interactive applications.
Roman Kern is the head of the Knowledge Discovery group and the main contact point.
The Knowledge Discovery group spans people from the Institute of Interactive Systems and Data Science and the Know-Center (research centre for Data-Driven Business and Artificial Intelligence). There are three sub-groups of Knowledge Discovery, each with a dedicated leader:
There are three options available:
Feel free to use the Latex thesis template (based on input from Karl Voit and Keith Andrews):
Collection of a few helpful tips for Master's thesis, provided by Annemarie Harzl. For printing the thesis one can choose the CopyShop or an online service (e.g., masterprint). After the thesis is finished beware of predatory publishers that offer to print the thesis for free!
List of open topics together with their domain - each topic can be chosen for either a Bachelor's or Master's thesis (emphasis and scope will be adapted)
Collect a textual dataset, split and pre-process the data. Each word is then clustered, and pure clustered are used to split the word and replace its occurrence with a cluster representation. Continue this process until no pure clusters can be found.
Goal: Find out, which words should be stemmed, and which should remain intact in a preprocessing pipeline. Approach: Define a set of criteria (hypothesis) for making such a decision. Then, devise a evaluation design to find out, what the best criteria (or combination) is.
Regular presentation and discussion of students works, e.g., Master's thesis.
Book a slot Just send an e-mail with your preferred date to rkern<at>tugraz.at, optimally including a title and a short abstract.
Date/time/location/speakers Should be in the details of the event - occasionally, there will also be friendly reminders of upcoming presentations.
Give a presentation The presentation typically are 20 minutes, allowing for approx. 5 minutes of Q&A - the language by default is English (German only in exceptional cases). Please bring your own laptop for the presentation.
Overview of recent research activities.
Selected papers and other dissemination activities.