Prof. Dr. Matthias Jarke - Theses
Master
A Recommender System for Decentralized Question-Based Dialog - Open
Supervised by PD Dr. Ralf Klamma, AOR, Prof. Dr. Matthias Jarke; Advisor(s):
Peter de Lange, M.Sc.,
Dr. Tracie Farrell,
Bernhard Göschlberger, MLBT MSc BSc
Bachelor
Model-Based View Extraction With GraphQL - Open
Supervised by Prof. Dr. Matthias Jarke, Prof. Dr. Bernhard Rumpe; Advisor(s):
Dr. István Koren,
Manuela Dalibor
Master
Predictive Modelling for High Pressure Die Casting Processes Using High Dimensional Feature Selection - Open
Supervised by Prof. Dr. Matthias Jarke, Prof. Dr. Peter Loosen; Advisor(s):
Arnab Chakrabarti, M.Sc.,
Prof. Dr. Christoph Quix,
Paul Buske
Master
A Neural Network Model for Visualization Recommendation System - Running
Supervised by Prof. Dr. Matthias Jarke, Prof. Gerhard Lakemeyer, Ph.D.; Advisor(s):
Arnab Chakrabarti, M.Sc.
A Recommendation Tool for Data Visualization using Artificial Neural Networks
Master
A Peer-to-Peer Service Framework With WebAssembly - Running
Supervised by PD Dr. Ralf Klamma, AOR, Prof. Dr. Matthias Jarke; Advisor(s):
Dr. István Koren
Bachelor
A Web-Based Best Practice Exchange Platform for the Shop Floor - Running
Supervised by Prof. Dr. Matthias Jarke, Günther Schuh; Advisor(s):
Dr. István Koren,
Stefan Braun, M. Sc. RWTH,
Niklas Rodemann
Master
An Evaluation Framework for High Dimensional Data Visualization - Running
Supervised by Prof. Dr. Matthias Jarke, Prof. Dr. Christoph Quix; Advisor(s):
Arnab Chakrabarti, M.Sc.
Bachelor
Chatbot-assisted Community Analysis - Running
Supervised by PD Dr. Ralf Klamma, AOR, Prof. Dr. Matthias Jarke; Advisor(s):
Alexander Tobias Neumann, M.Sc.
The goal of this thesis is a chatbot that can be used by a community to query usage data and visualizations from an existing system.
Bachelor
Data Analysis of Micromobility in the City of Aachen - Running
Supervised by Prof. Dr. Matthias Jarke; Advisor(s):
Felix Schwinger, M. Sc.
This thesis focuses on the data analysis of micromobility data in Aachen. The goal is to use data science methods to gain insights from the already gathered data. To this end, a suitable data model should be defined, which then enables the analysis of both station-based, free-floating and hybrid shared mobility modes. On this defined data basis, various analyses should be performed.
Master
Detecting Appliances and Faults in Appliances based on Power Usage Data - Running
Supervised by Prof. Dr. Matthias Jarke, Prof. Dr. Thomas Berlage; Advisor(s):
Karl Catewicz
Bachelor
Disaggregating Traffic Demand Data for Agent-Based Traffic Simulations - Running
Supervised by Prof. Dr. Matthias Jarke, Prof. Wolfgang Prinz, Ph.D; Advisor(s):
Felix Schwinger, M. Sc.
Traditional Traffic Demand Analysis as implemented in most commercial tools operate given variations of the so called four-step model. During this four-stepped modelling process origin-destination matrices are generated as output. With a rising amount of computation power, so called agent-based simulation tools are emerging. Here the traffic demand is not generated using a statistical model, but the decisions of each agent is evaluated in a simulation framework. In agent-based simulation frameworks more information is necessary, for example, complete activity chains for each agent. In this thesis a novel method for generating activity chains from origin-desination matrices is explored and compared with traditional demand forecasting methods.
Bachelor, Master
Bachelor
Linking DevOps Tools to Social Requirements Engineering - Running
Supervised by Prof. Dr. Matthias Jarke, PD Dr. Ralf Klamma, AOR; Advisor(s):
Dr. István Koren
Master
Recognition of Anomalous Behavior in the Context of Access Control System - Running
Supervised by Prof. Dr. Matthias Jarke, Prof. Dr. Christoph Quix; Advisor(s):
Dr. Rihan Hai,
Bachelor, Master
Text Mining Techniques for Student Assessments - Running
Supervised by Prof. Dr. Matthias Jarke; Advisor(s):
Peter de Lange, M.Sc.,
Alexander Tobias Neumann, M.Sc.
The goal of this thesis is to integrate the open-source framework ReaderBench into the Kubernetes cluster of the tech4comp project. The thesis should investigate related work in the domain of text mining, natural language processing and educational data mining. The developed extension should integrate into the existing project's infrastructure and provide mentees and their mentors/tutors with advanced feedback on the mentee's reading comprehension.
SmartGreens 2021 Conference Chair 