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Prof. Dr. M. Jarke
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Prof. Dr. M. Jarke
RWTH Aachen
Informatik 5
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Open Theses  


Master
Process Interaction across Blockchains
Posted on 10. Nov 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
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
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
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).
Bachelor, Master
Optimizing Mining Maximal Frequent Patterns with MFPAS
Posted on 29. Sep 2017; Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez, Rezaul Karim
Recently, a new approach for finding maximal frequent patterns (MFPAS) was presented by the supervisor and advisers of this thesis. Several further optimizations of the algorithm are possible. The student working on this thesis will experiment with different optimization possibilities and analyse their effect experimentally. For a master thesis, further theoretical analysis of the optimizations and the original algorithm are necessary.
Master
Service Provisioning for Mobile Edge Cloud Computing
Posted on 29. Sep 2017; Supervised by PD Dr. Ralf Klamma, AOR
Mobile edge cloud computing provides a platform to accommodate the offloaded traffic workload generated by mobile devices. It can significantly reduce the access delay for mobile application users. However, the high user mobility brings significant challenges to the service provisioning for mobile users, especially for the delay-sensitive mobile applications. We want to research how to update the service provisioning solution for a given community of mobile users. Therefore, we compare current offloading strategies, information structures based on peer-to-peer in combination with cloud computing and client-side solutions using advanced Web protocols like WebRTC. The thesis continues our successful research record in mobile cloud computing,
Bachelor, Master
Social Recommender Systems for Professional Communities
Posted on 11. Nov 2013; Supervised by PD Dr. Ralf Klamma, AOR
This thesis aims to develop social recommender system service for Open Source Software (OSS) Communities.
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
Measuring coherence accross media in learning environments
Posted on 28. Sep 2017; Supervised by PD Dr. Ralf Klamma, AOR, Dr. Marc Spaniol
Computer linguistics has provided impressive results for measuring the quality of writing, e.g. for automatic essay scoring. 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. 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 prototypical combine a few of these computational methods for one or two analysis scenarios, e.g. a MOOC or a webinar.
Bachelor, Master
Mobility Service Payment using Privacy-Preserving Interval Operations
Posted on 17. Nov 2017; Supervised by Prof. Dr. Matthias Jarke, Prof. Dr. Ulrike Meyer; Advisor(s): Dipl.-Inform. Christian Samsel, Dipl.-Kfm. Markus Christian Beutel, Stefan Wüller
Together with the IT security chair, we'd like to investigate the possibilities of employing cryptographic oprations for bartering in ride sharing scenarios.
Bachelor
Evaluation of Stream Sampling Algorithms
Posted on 08. Feb 2017; Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez
The student will implement several stream sampling algorithms and perform experiments to compare their performance. The implementations are done on top of streaming frameworks like Spark, Apache Flink, and Storm.
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
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
Accelerating Graph Embedding using GPUs and Distributed Computing
Posted on 29. Sep 2017; Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez, Rezaul Karim
Lately several methods for embedding graphs nodes into a vector space have been proposed. These embeddings can then used to train other machine learning models. Learning these embeddings is typically done using CPUs. In this thesis the student would look into the use of other hardware, like GPUs and distributed computation options to speed up the learning process. The challenge is that algorithms working on graphs have typically a bad memory locality. Hence, existing algorithms might need profound modification in order to use them on GPUs or in a distributed fashion.
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.
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
Evaluating the performance of all-pairs personalized page rank
Posted on 23. Oct 2017; Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez
Recently, a new approach for computing the personalized pagerank (PPR) for all nodes in a graph was presented by the adviser of this thesis. Personalized pagerank can be used to determine how important specific nodes in a graph are from the viewpoint of a specific node, or set of nodes. For example, it can be used to determine which web pages are relevant for a user, given a set of pages he has visited before. The improvement which the advisor of the thesis devised is useful when the PPR has to be computed for all nodes in the graph. The gain in speed is due to reuse of already computed PPR values for other nodes and a clever ordering of nodes. The student working on this thesis will experiment with this technique and others. First, the student needs to investigate ways to parallelize the algorithms and analyse the algorithms and their parameters experimentally.
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
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.
Master
Travel Assistance using Natural Language
Posted on 12. Oct 2017; Supervised by Prof. Dr. Matthias Jarke; Advisor(s): Dipl.-Inform. Christian Samsel, Dr. Karl-Heinz Krempels
Previously, we developed approaches and solutions for travel assistance using e.g. a wearable device, as well as a prototype for a natural language travel information system. We'd like to combine these two approaches into a combined prototype and test it in the field.
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, Master
Including Attributes in a Graph Embedding
Posted on 29. Sep 2017; Supervised by Prof. Dr. Stefan Decker; Advisor(s): Dr. Michael Cochez
Lately several methods for embedding graphs nodes into a vector space have been proposed. These embeddings can then used to train other machine learning models. Most approaches will, however, only keep relations between nodes representing entities in the graph into account. If the graph also has nodes representing literal values (numbers, strings, etc.) then they are ignored. In this thesis, the student will investigate how these attributes can be included in the embedding.
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.
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.