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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
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Theses

Information about Diploma/Master thesis process

Open Theses  


Master
Activity Dialog Service
Intelligent agenda planning systems create itineraries for users based on their appointments and activities. The objective of the thesis is the analysis of the user planning task for appointments and activities, the design of a semantic model for the user dialog with an appointment and activity planning system. As proof of concept a functional prototype should be implemented and evaluated.
Master
Analyzing distributed ledger data structures for the immutable persistence of transactions and tamper-secure execution of processes
Posted on 31.08.2018; Supervised by Prof. Dr. Thomas Rose; Advisor(s): Thomas Osterland
Often only noticed as a technology that enables the digital currency Bitcoin, blockchain is a novel protocol that allows the distributed and secure storing of information and untampered execution of program code in trust-less environments. As part of a broader range of technologies that allow the immutable storage of information in decentralized networks, where network participants build a consensus about the correctness of persisted information, the classical blockchain is only one specific implementation of distributed ledger technologies. Other ledger technologies are based on directed acyclic graphs (DAGs). Topic of this thesis is the exploration and implementation of a DAG based ledger in the existing blockchain framework Labchain (https://github.com/putschli/LabChain).
Master
Collaborative Immersive Learning Analytics
Posted on 01.07.2019; Supervised by PD Dr. Ralf Klamma, AOR
Our approach is a comprehensive and evolutionary sociotechnological learning analytics and design process leading to a flexible infrastructure where professional communities can co-create their wearable enhanced learning solution.
Bachelor
Developing a Data Annotation Tool for Scientific Data Management
Posted on 25.10.2016; Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Oya Deniz Beyan
Semantic technologies and RDF data representation can improve the reusability of scientific data and enable scientist to reproduce the experiments. However there is no tool to support researcher for making their data semantically interpretable by computers. Aim of the thesis is to understand the benefits of semantic web technologies for reproducible research and develop a tool which can convert experimental data to RDF by annotating with selected data models.
Bachelor, Master
Master
Exploring Unknown Environments - Finding Pollution in Underground Pipes
Posted on 16.11.2018; Supervised by Prof. Dr.-Ing. Gerd Ascheid, Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez, Ahmed Hallawa
Master
Interactive Support for Business Modelling
Posted on 21.06.2017; Supervised by Prof. Dr. Thomas Rose; Advisor(s): Thomas Osterland
A business model is an abstract model of the business of one or more cooperating organisations. It is a conceptual and architectural implementation of a business strategy and the foundation for the implementation of business processes and information systems. The research objective of this thesis is the design, implementation and evaluation of an interactive tool for the engineering of a business model.
Master
Measuring coherence accross media in learning environments
Posted on 28.09.2017; Supervised by PD Dr. Ralf Klamma, AOR, Prof. Dr. Marc Spaniol
Multimedia content based indexing delivered a lot of models for the analysis of multimedia materials. In modern educational platforms, e.g. MOOCs and self-regulated learning platforms. In consequence, multimedia materials are produced by educational designers but also by the learners during their learning processes. Coherence is a semantic measure for the local and global connectivity of e.g. sentences, paragraphs, videos, slides among others. Computer linguistics has provided impressive results for measuring the quality of writing, e.g. for automatic essay scoring. To measure the coherence of multimedia materials many computational methods reaching from natural language processing to machine learning needs to be combined in a common coherence model. Goal of this master thesis is to co-develop a coherence model for cross-media coherence and to prototypically combine these computational methods for a webinar.
Bachelor, Master
Master
Next-generation Sequencing Using Data Lakes - MA / BA
Posted on 17.10.2017; Supervised by Prof. Dr. Thomas Berlage, Prof. Dr. Christoph Quix; Advisor(s): Dr. Sandra Geisler, Tillmann Eitelberg
NGS Pipeline on Azure Data Lake The development of next-generation sequencing (NGS) technologies at the beginning of the 21st century opened the door for revolutionary study setups which enables access to a long time closed dimension of knowledge in several fields of research like genetics, ecology and medicine. The so called “Ppipeline” is the link between different work steps and corresponding tools within the workflow when analyzing a NGS dataset. Microsoft Azure Data Lake is based on two different services. The Azure Data Lake Store allows to store different types of data in an almost unlimited size. With Azure Data Lake Analytics it’s possible to run massively parallel data transformation and processing programs massively in U-SQL, R, Python, and .NET over petabytes of data stored in the Azure Data Lake Store. In our company, we develop the system BOA , a Pipeline based on Microsoft Azure Data Lake designed for analyzing NGS datasets. In order to achieve maximum performance and optimal results, the data for the various steps are partitioned and analyzed using different algorithms. The input and output of the data within BOA is done via a user-friendly user interface. In addition, the system offers the possibility to analyze the data directly against various reference databases. The goals of this thesis are: - to evaluate different algorithms for data partitioning in the context von RNA sequences - to evaluate different algorithms in different languages (C#, R, Python) to optimize the performance in sequence alignment - to design and implement an incremental loading process of different RNA reference databases for the alignment process
Master
Process Interaction across Blockchains
Posted on 10.11.2017; Supervised by Prof. Dr. Thomas Rose; Advisor(s): Thomas Osterland
FIT and Bosch offer in collaboration two Master Theses: Combination of different application specific blockchains and registry of services governed by blockchains
Master
Process model-oriented creation of smart contracts
Posted on 31.08.2018; Supervised by Prof. Dr. Thomas Rose; Advisor(s): Thomas Osterland
Often only noticed as a technology that enables the digital currency Bitcoin, blockchain is a novel protocol that allows the distributed and secure storing of information and untempered execution of program code in trust-less environments. Did you ever feel the intense desire to write a thesis about blockchain or do you have a slight hope that blockchain is the one-and-only topic that touches your heart? Use your chance now! We are looking forward to hear from you.
Master
Reservation, Booking and Customer Hotline Dialog Service
Reservation, booking and customer hotline services are based on context based dialog management. The objective of the thesis is the analysis of user interactions for different contexts in reservation, booking and customer hotline situations with a dialog management system and the design and implementation of a semantic model for the user dialog with a dialog management system. As proof of concept a functional prototype should be implemented and evaluated.
Master
Simulating the dynamics of interacting blockchain nodes
Posted on 31.08.2018; Supervised by Prof. Dr. Thomas Rose; Advisor(s): Thomas Osterland
Often only noticed as a technology that enables the digital currency Bitcoin, blockchain is a novel protocol that allows the distributed and secure storing of information and untempered execution of program code in trust-less environments. Did you ever feel the intense desire to write a thesis about blockchain or do you have a slight hope that blockchain is the one-and-only topic that touches your heart? Use your chance now! We are looking forward to hear from you.
Master
Simulation tools for the Assessment of Emergency Management Processes
Posted on 12.09.2018; Supervised by Prof. Dr. Thomas Rose; Advisor(s): Thomas Osterland
Large scale disasters represent a major challenge for any medical service. Typically such disasters, be they founded in terrorism, natural or technical catastrophize, generate a significant number of casualties (MASCAL – Mass Casualty) with severe and unusual injury patterns. Many processes are supported by Standard Operating Procedures as common practice, but any catastrophe requires a change of processes due to the nature of the disaster and thus furnishes a major challenge for hospital operations. As of now, hospitals and medical services are designed for a specific workload that has been agreed among different stakeholders. Hence, processes and their resources are designed in light of best practices for patient care as well as anticipated workload.
Master
Travel Information Dialog Service
Travel information services provide itinerary and context based user travel assistance. The objective of the thesis is the analysis of user interactions for different contexts in intermodal travel situations with a travel information assistance system and the design and implementation of a semantic model for the user dialog with a travel information assistance system. As proof of concept a functional prototype should be implemented and evaluated.
Master
User Digital Assistant Dialog Service
Intelligent user assistant agents and chatbots provide task based interactions and functionality to the user. The objective of the thesis is the user interaction analysis for a given set of tasks, the design of a suitable dialog service based on a semantic knowledge model, and the implementation and evaluation of a functional prototype.

Running Theses


Bachelor
Machine Learning for Anonymization of Unstructured Text
Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez
This thesis addresses the problem of identifying personal information in unstructured text using supervised Machine Learning (ML). The final application should be able to recognize and annotate the tokens that make up personal data in an English input text as accurately as possible. First, supervised learning methods, suitable for the task, will be identified. Then, models based on the most promising approaches will be designed and implemented. For comparison, suitable evaluation metrics have to be determined. Finally, the approaches are compared and evaluated against a baseline and each other.
Master
Privacy Attack on Social Networks Using Network Embeddings
Supervised by Prof. Dr. Markus Strohmaier, Prof. Dr. Stefan Decker; Advisor(s): Dr. Florian Lemmerich, Dr. Michael Cochez
Abstract. A company that runs a social network trains a node embedding on the network where each account is represented by one node. One user deletes his account. Thus, the company is legally required to remove all private information of that user. This includes the node associated with the user’s account and the vector representation of that node that is generated by the embedding. The company, however, does likely not delete the vector representations of the other nodes even though the removed node was used during training of these. Is it possible to identify the neighbors of the removed node? Which kinds of neighbors can be identified best, which cannot be identified? First results suggest that the identification of neighbors works well for some kind of nodes and is more difficult for others.

Completed Theses


Bachelor
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.
Master
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).