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Informatik 5
Information Systems
Prof. Dr. M. Jarke
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Prof. Dr. M. Jarke
RWTH Aachen
Informatik 5
Ahornstr. 55
D-52056 Aachen
Tel +49/241/8021501
Fax +49/241/8022321

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Completed Theses

Datenanalyse zur Fehlererkennung im Präparationsauftrag des Schmelzspinnprozesses
Friedrich May in 2020; Supervised by Prof. Dr. Stefan Decker, Thomas Gries; Advisor(s): Dr. Sandra Geisler, Lukasz Debicki
Continuous Community Analytics
Clemens Kersjes in 2020; Supervised by PD Dr. Ralf Klamma, AOR
Goal of this thesis is an integration of post-mortem community data dumps with the MobSOS real-time community information systems success awareness framework.
A Multimodal Mentoring Cockpit for Tutor Support
Learning analytics aim at providing an insight into the student’s learning process such that individual performance can be measured and thus provide the basis for individual student support. This thesis will utilize and evaluate existing mentoring solutions and aggregate them in a state-of-the-art progressive Web application. The outcome of this thesis will be a newly developed mentoring cockpit that meets the requirements of a holistic mentoring support experience.
Bachelor, Master
Distributed Activity Coordination with Constraints
In cooperative user environments the distributed coordination of activities with hard and soft constraints is a challenging task. The objective of the thesis is the development of an heuristic for distributed coordination of activities with hard and soft constraints starting with a literature research, algorithm design and simulative evaluation.
Concept embeddings for Wikipedia across language editions
Felix Ingenerf in 2019; Supervised by Prof. Dr. Markus Strohmaier, Prof. Dr. Stefan Decker; Advisor(s): Dr. Florian Lemmerich, Dr. Michael Cochez
Wikipedia is a free and openly available source of information curated by users. The content available varies between language versions. The question is now whether the content available, and specifically the associations between articles, is dependent or influenced by cultural differences between users (readers and editors) in different parts of the world. In this thesis the student investigates whether these could be found trough graph embeddings which are created on the Wikipedia link graph, the graph formed by interactions with Wikipedia and a graph formed by measuring similarity between pages.
Deep Learning-based Knee Osteoarthritis Diagnosis from Radiographs and Magnetic Resonance Images
In this thesis, the student investigates the use of deep learning techniques (especially computer vision) to perform diagnosis of osteoarthritis. The input to the system are both radiographs (X-RAY) and magnetic resonance images (MRI).
Identifying Media-Specific and Time-Dependent Patterns in Community Success Models
Jia Lai in 2019; Supervised by PD Dr. Ralf Klamma, AOR, Prof. Dr. Matthias Jarke
Assuming that best practices for organizing work and learning emerge from the visual analytics and comparison of real communities, the goal of this thesis is to analyze media transcription processes from real communities using data mining and machine learning.
Classification of Mechanically Ventilated Patients Based on Weaning Difficulty
Ilias Spyros in 2019; Supervised by Prof. Dr. Christoph Quix, Johannes Bickenbach; Advisor(s): Dr. Sandra Geisler, Jermain Kaminski, Arne Peine
Classification of Cancer with methylation aware motifs
Gehrmann, Julia in 2019; Supervised by Prof. Dr. Stefan Decker, Ivan Gesteira Costa Filho; Advisor(s): Dr. Oya Deniz Beyan, Md. Rezaul Karim, M.Sc.
This dissertation addresses the problem of classification of cancer patients from DNA methylation. Mrs. Gehrman explores here the use of scores of transcription factors binding sites around DNA methylation as surrogate markers for DNA methylation. An innovative aspect is the fact binding site motifs take into consideration of the DNA methylation status of a given locus. Next, this work compared the performance of machine learning classifiers either using classical DNA methylation levels vs. TF binding affinity scores. For this, several classical machine learning methods (SVM, inductive trees, random forests) were used. Performance accuracy was similar with both data representations, however the computational time of training classifiers with TF binding site affinity scores were at least 10 times fasters, due to the lower dimensionality of the new space. This works supports promising features of DNA methylation aware TF binding scores.
Chat Interfaces for Social Bots in a Peer-to-Peer Environment
Social Bots (software robots) are computer algorithms that automatically produce content and interact with humans on social media. This thesis will utilize and evaluate a social bot framework with different community applications. It will also extend the framework to support two-way chat interfaces with the system via common chat applications (e.g. Slack).
Context based Travel Information Service
Travel information services provide itinerary based user travel assistance. The objective of the thesis is the user context analysis for multimodal travel situations, the design of a mobile device based context detection service and an information rendering service for user travel assistance. As proof of concept a functional prototype should be implemented and evaluated.