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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
A Platform for Creating Social Bots
Posted on 26. Jul 2016; Supervised by PD Dr. Ralf Klamma, AOR
Social Bots (software robots) are computer algorithms that automatically produce content and interact with humans on social media.
Bachelor
An Editor for Prototype-based Knowledge Bases
Posted on 24. Oct 2016; Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez
Prototype ontologies are a new approach for knowledge representation. The task of the student is to create an editor for prototype based ontologies, based on the prototype knowledge base code provided. The editor must be intuitive to use and give suggestions to the user. Further, it must show how final values of the prototypes have been derived.
Bachelor
Automatic for the People - Open Badge based Learning Assessment
Posted on 10. Jun 2015; Supervised by PD Dr. Ralf Klamma, AOR
Assigning automatically badges that reflect the learning progress of self-directed learners.
Master
Blockchain
Posted on 21. Jun 2017; 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.
Bachelor, Master
Bachelor
Comparing Communities and Topics in Wikipedias
Posted on 11. Sep 2017; Supervised by PD Dr. Ralf Klamma, AOR; Advisor(s): Bernhard Göschlberger, MLBT MSc BSc, Mohsen Shahriari
Investigate the relationship between communities and topics by applying overlapping community detection to the social network of contributors and subsets of intrawiki link networks on different Wikipedias.
Bachelor, Master
Conversion from RDF to Prototype-based Knowledge Base
Posted on 24. Oct 2016; Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez
Prototypes have been proposed recently as a new way to represent knowledge. In recent years many datasets have been published using RDF. Your task is to find out how the RDF dataset can be converted to prototypes in an efficient manner. For a master thesis, you also have to work on the optimal conversion for different requirements such as updates in the original RDF data.
Bachelor
Developing a Data Annotation Tool for Scientific Data Management
Posted on 25. Oct 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
Developing a Linked Open Data Registry plugin for Taverna Workflows
Posted on 25. Oct 2016; Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Oya Deniz Beyan
Analyzing and processing open RDF data sources is vital for stimulating new discoveries in medicine. The Taverna workflow management system is an Apache incubator project ( https://taverna.incubator.apache.org/ ). The system enables scientist to create and store re-executable data analytics workflows which are described in the XML-based language SCUFL. Taverna is adopted by many research groups working in a variety of fields including bioinformatics (such as transcriptomics, proteomics and metabolomics), text mining, biodiversity and the Virtual Physiological Human. For life scientists, it is important to access distributed, changing sources such as Bio2RDF and DisGeNET-RDF to improve their outcomes. In this thesis, a Taverna plug-in will be developed to access open RDF data sources. The plug-in will browse services in RDF endpoints, query metadata, and add them to Taverna workflows.
Bachelor
Evaluation of Approximate Hierarchical Clustering Algorithms
Posted on 29. May 2017; Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez
There are several algorithms to perform a hierarchical clustering, resulting in approximate dendrogram. This makes it possible to perform a clustering on big data sets. In this thesis the student will evaluate of several existing algorithms in terms of resource use and clustering quality. As part of this work, the student has to implement some of the algorithms to work on a GPU as they are not scalable enough for CPU computing.
Bachelor, Master
Extending Private Information Retrieval (PIR) for Privacy Enabling Personalisation
Posted on 05. May 2017; Supervised by Prof. Dr. Stefan Decker; Advisor(s): Benjamin Heitmann, Ph.D.
PIR is an approach for database queries in which the database can neither see the query nor the result, yet it can trust that constraints such as access control are followed. Can this be extended to enable personalisation if the query represents a user profile, and the constraints represent the logic/rules of the recommender system?
Master
Immutability for Prototype-based Knowledge Bases
Posted on 24. Oct 2016; Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez
Prototypes have been proposed recently as a new way to represent knowledge. Typically, one allow any kind of changes in a dataset. However, when a dataset is distributed with potentially malicious parties, it would be beneficial to make the dataset immutable and use some form of signature to prove authenticity. Moreover, making the data immutable has beneficial properties for caching. In the immutable scenario, the only way to make changes is by adding more prototypes. The student's task is to investigate the different options to make this immutable prototype store happen. This requires studying things like block chains and the internal git storage model. Further, the thesis can include some mechanisms to simulate some sort of mutability (e.g. by combining immutable and mutable parts).
Master
Interactive Support for Business Modelling
Posted on 21. Jun 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
It's the Media, Stupid: Identifying Media-Specific and Time-Dependent Patterns in Community Success Models
Posted on 31. May 2016; Supervised by PD Dr. Ralf Klamma, AOR
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.
Master
Locality-sensitive Hashing using not-so-random Hash Functions
Posted on 24. Oct 2016; Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez
Locality-sensitive hashing is used to speed up near-neighbor search in high dimensional space. When the distance of interest is cosine distance, Random hyperplane hashing (RHH) is used. This technique is based on randomly selecting hyperplanes. However, in some cases (when we have more information about the dataset) it seems reasonable to not choose the hyperplanes completely randomly. Further, if normal RRH is performed with a low number of hyperplanes, then the hyperplanes are likely to not cover the space very well. This thesis will be about choosing the hyperplane in a data dependent way and try to sample the hyperplanes such that they cover the space nicely (including a comparison with angular quantization).
Master
Locality-sensitive Hashing with Undecisive Hash Functions
Posted on 24. Oct 2016; Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez
Locality-sensitive hashing (LSH) is used to speed up near-neighbor search in high dimensional space. LSH works by hashing the elements to discrete buckets. However, in some cases the hash function has to make a decision which leads to similar points being hashed apart. This, for instance, happens when a point is close to a hyperplane in RHH. One solution to this problem is to hash several small perturbations of the points and insert all of them into the indexes. Other solutions also exist. This thesis will look into the different options for improving the performance of LSH by hashing points to multiple buckets instead of just one.
Master
Post-Mortem Community Information Systems Success Analytics
Posted on 31. May 2016; 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.
Bachelor, Master
Secure Evaluation of Knowledge Graph Merging Gain
Posted on 08. Aug 2017; Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez, Benjamin Heitmann, Ph.D.
Alice wants to sell a knowledge graph (KG) to Bob, who wants to use it to extend his own KG. Bob wants to know how much it should pay Alice for the data. The only way seems to be that Alice gives her KG to Bob for evaluation. The problem is now that Alice cannot know that Bob is not going to keep the dataset. In this thesis, the student will look into algorithms to securely estimate the gain from combining these two KGs without actually sharing them.
Bachelor, Master
Sensor Fusion for AR Devices in Training
Posted on 31. Aug 2017; Supervised by PD Dr. Ralf Klamma, AOR, Roland Klemke; Advisor(s): Dipl.-Medieninf. István Koren
An immersive Augmented Reality (AR training development framework needs support for combinations of a wide range of appropriate devices for different use cases. In a surgery training situation this can be an AR headset and a handtracking device capturing exact movements in order to evaluate the accuracy. Therefore, it is necessary to get information from different sensors and interpret them in a common sensor fusion framework, in order to record the actions. The goal of the thesis is twofold. First, the WEKIT.one framework will be extended. New sensor hardware, which can be used to improve the training experience of apprentices, will be implemented, tested and evaluated against the given requirements. The implementation is based on the Unity SDK in combination with Microsoft HoloLens and other AR relevant devices. Second, we are interested in visual learning analytics of the gathered data. Therefore, means for storing learner traces both locally and externally will be evaluated with the intention to use the stored data for long-term analytics. Contributions will be specified and implemented with the help of the upcoming IEEE standard on Augmented Reality Learning Experience Models (ARLEM). As a Bachelor thesis, the scope can be adjusted.
Bachelor, Master
Using Functional Encryption for Privacy Enabling Personalisation
Posted on 05. May 2017; Supervised by Prof. Dr. Stefan Decker; Advisor(s): Benjamin Heitmann, Ph.D.
Functional encryption is an emerging approach for encrypting data in a way which allows executing an a priori specified function on the encrypted data. While FHE/SMPC allows general functions to be executed, for functional encryption, one function needs to be specified beforehand, and only that function can be executed on the encrypted data. Can this be used as part of a personalisation process?

Running Theses


Bachelor
A Gamification Framework for Mixed Reality Training
Supervised by PD Dr. Ralf Klamma, AOR, Dr. Andreas Herrler; Advisor(s): Dipl.-Medieninf. István Koren
In this thesis a framework will be developed which enables a gamified approach to training and learning in a mixed reality environment. The framework targets the Microsoft HoloLens and uses the Unity 3D Engine. It will support the 3D models of the Anatomy 2.0 web-application. Moreover, the framework can be customized by adding additional models in X3D-format. Furthermore, this work will explore the current gamification approaches and how they can be employed in mixed reality. Those methods and features will be elaborated in a medical use-case. It will provide a learning environment which can visualize and gamify the study of the human anatomy.

Completed Theses


Master
Integration of On-Demand Buses Into Intermodal Travel Information
Our chair is developing the intermodal travel information system MobilityBroker in cooperation with IVU, regioIT and ASEAG. We would like you to create a concept and implement the integration of on-demand bus services into the existing system.