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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
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Theses

Information about Diploma/Master thesis process

Open Theses  


Bachelor, Master
"Why peers leave or change communities?" experiments using the GPU-based community detection and evolution library
Posted on 14. Jan 2016; Supervised by Prof. Dr. Matthias Jarke; Advisor(s): Dr. Zinayida Petrushyna (Kensche), M.Sc.
The GPU-based community detection and evolution library was developed in the chair and shows more efficient results comparing to implementations of same algorithms using CPU. Therefore, it allows us to perform a number of experiments on different data sets of communities (Facebook, Twitter, e-mail network, forum networks) to understand reasons community members stay or leave in their communities. This work aims to find computational models (based on machine learning) that describe behaviors of the members.
Master
(De) & Centralized Services for Storing Learner Models
Posted on 13. May 2015; Supervised by PD Dr. Ralf Klamma, AOR, Prof. Dr. Matthias Jarke; Advisor(s): Kateryna Neulinger, M.Sc.
This master thesis is aimed to answer the research question: "How to best store learner-specific information to achieve better accessibility, security, reusability and retrieval time?" For this purpose the client-server, peer-to-peer (p2p) architectures will be implemented and compared.
Bachelor, Master
A Novel Architecture for Learner’s Profiles Exchange
Posted on 30. Oct 2015; Supervised by PD Dr. Ralf Klamma, AOR, Prof. Dr. Matthias Jarke; Advisor(s): Kateryna Neulinger, M.Sc.
The purpose of this thesis is to propose a novel architecture with a common user profile for the educational domain, allowing the exchange user specific data between different adaptive educational systems.
Bachelor
Advanced Modeling for Travel Chain Recommendations
Posted on 08. Dec 2015; Supervised by Prof. Dr. Matthias Jarke; Advisor(s): Dipl.-Inform. Christian Samsel, Dr. Karl-Heinz Krempels
We developed a personalized and context-aware recommendation system to simplify the selection of intermodal itineraries. Currently the models of users, context and itineraries are quiet simple. We'd like you to enrich the used models with additional properties and assess which of them are helpful to create satisfying recommendations.
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
Implementing Pregel for a Multi Model Database
Posted on 14. Dec 2013; Supervised by PD Dr. Ralf Klamma, AOR, Prof. Dr. Matthias Jarke; Advisor(s): Dr. Frank Celler (triAGENS GmbH)
The goal of this thesis is to implement functionality for a multi model database to run established graph algorithms parallelized.
Bachelor
Integrating Car Entertainment Systems into Intermodal Travelinformation
Posted on 18. Jan 2016; Supervised by Prof. Dr. Matthias Jarke; Advisor(s): Dipl.-Inform. Christian Samsel, Dr. Karl-Heinz Krempels
In our previous and running projects we developed intermodal travelinformation systems combining various modes of transportation (public transport, carsharing, bikesharing, electric charging etc) on a single plattform. Still missing is the integration of a mondern car entertainment systems with such a plattform. We'd like you to develop a prototype for a car app plattform integrating the internal navigation with an advanced intermodal travel information systems using standardized interfaces.
Master
Integration of Parking Information into Travel Information Systems
We want you to integrate parking information into travel information systems and evaluate related user perceptions.
Master
Learning Analytics platform for Personal Learning Environments
Posted on 05. Nov 2013; Supervised by PD Dr. Ralf Klamma, AOR; Advisor(s): Dr. Milos Kravcik
The aim is to develop a platform that collects relevant data from learning processes and visualizes it in a meaningful way in order to support different target groups – learners, teachers, and researchers/developers.
Bachelor
Near real-time community analysis using TensorFlow
Posted on 14. Jan 2016; Supervised by Prof. Dr. Matthias Jarke; Advisor(s): Dr. Zinayida Petrushyna (Kensche), M.Sc.
In November, 2015 Google opens a library for performing numerical computations with data. Using it a student need to implement existing algorithms for data analysis to extract interesting information like community interests or influential users in communities.

Running Theses


Master
A Comparative Study of Data Transformation Technologies between Heterogenous Data Stores
Companies today are beginning to reap the benefits of big data to improve revenues, control costs, and to find new business opportunities. For businesses that are waking up to the realization that data is a valuable asset that they need to exploit, the current technology boom does not disappoint them. The big data platform hosts a multitude of technologies that offer different processing capabilities to satisfy every user’s requirement. In this age of innovation where technologies invented yesterday are becoming obsolete, it is of utmost importance for firms to be up to date and switch to modern platforms with better processing capabilities. In this scenario thus, it is necessary to know the means of data transformations between these platforms. Further, data transformation also finds its utilization in “data exchange” which is the process of taking data structured under a source schema and transforming it into data structured under a target schema.While much has been done in describing the platforms and tools in great depth, however there exists no guide to the comparative study of data transformation between different big data platforms. This master thesis work is steered particularly into the comparison of data transformation between the most widely used platforms and tools which will be used to effectively select methodologies amid different players in the industry willing to exchange electronic data directly among themselves
Bachelor
Real-time Trajectory Mining in the Internet of Things
Supervised by PD Dr. Ralf Klamma, AOR, Prof. Jörg Blankenbach
In this thesis a system shall be developed to efficiently perform preprocessing tasks like map matching of trajectory data, while focusing on the demand for IoT device specific integration. So, the system will implement the light weight communication protocol MQTT. Open source tools that allow distributed computation will be used to achieve scalability, which is extremely important when considering the huge growth of sensor data and devices deployed.

Completed Theses